{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data\partyleaderslog.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res}12 Nov 2025, 15:04:30
{txt}
{com}. 
. *Preparing data set for analyses
. clear
{txt}
{com}. use "CVP_1_117.dta"
{txt}
{com}. keep chamber congress icpsr party cvp_gls_adjusted
{txt}
{com}. g house = chamber == "House"
{txt}
{com}. keep if party == 100 | party == 200
{txt}(7,087 observations deleted)

{com}. g dem = party == 100
{txt}
{com}. drop party chamber
{txt}
{com}. rename cvp cvp
{res}{txt}
{com}. merge m:1 icpsr dem house using "HouseSenateLeaders.dta"
{res}{txt}{p 0 7 2}
(variable
{bf:icpsr} was {bf:long}, now {bf:double} to accommodate using data's values)
{p_end}

{col 5}Result{col 33}Number of obs
{col 5}{hline 41}
{col 5}Not matched{col 30}{res}          41,922
{txt}{col 9}from master{col 30}{res}          41,922{txt}  (_merge==1)
{col 9}from using{col 30}{res}               0{txt}  (_merge==2)

{col 5}Matched{col 30}{res}             495{txt}  (_merge==3)
{col 5}{hline 41}

{com}. preserve
{txt}
{com}. *extract leader ideologies
. keep if _merge == 3
{txt}(41,922 observations deleted)

{com}. drop _merge
{txt}
{com}. drop if congress >= mincong
{txt}(187 observations deleted)

{com}. collapse (mean) cvp house dem, by(icpsr)
{res}{txt}
{com}. merge 1:1 icpsr house dem using "HouseSenateLeaders.dta"
{res}
{txt}{col 5}Result{col 33}Number of obs
{col 5}{hline 41}
{col 5}Not matched{col 30}{res}               0
{txt}{col 5}Matched{col 30}{res}              39{txt}  (_merge==3)
{col 5}{hline 41}

{com}. drop _merge
{txt}
{com}. rename mincong cong0
{res}{txt}
{com}. forvalues i = 1/15 {c -(}
{txt}  2{com}. g cong`i' = cong0 + `i' if cong0 + `i' <= maxcong 
{txt}  3{com}. {c )-}
{txt}(3 missing values generated)
(9 missing values generated)
(17 missing values generated)
(25 missing values generated)
(30 missing values generated)
(33 missing values generated)
(34 missing values generated)
(36 missing values generated)
(36 missing values generated)
(38 missing values generated)
(39 missing values generated)
(39 missing values generated)
(39 missing values generated)
(39 missing values generated)
(39 missing values generated)

{com}. drop maxcong
{txt}
{com}. reshape long cong, i(icpsr) j(num)
{res}{txt}(j = 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15)

Data{col 36}Wide{col 43}->{col 48}Long
{hline 77}
Number of observations     {res}          39   {txt}->   {res}624         
{txt}Number of variables        {res}          20   {txt}->   {res}6           
{txt}j variable (16 values)                    ->   {res}num
{txt}xij variables:
                 {res}cong0 cong1 ... cong15   {txt}->   {res}cong
{txt}{hline 77}

{com}. drop if cong == .
{txt}(456 observations deleted)

{com}. drop num icpsr 
{txt}
{com}. sort house dem cong 
{txt}
{com}. rename cvp leader_cvp
{res}{txt}
{com}. g leader_next = leader_cvp[_n+1] if house == house[_n+1] & dem == dem[_n+1]
{txt}(4 missing values generated)

{com}. g leader_prev = leader_cvp[_n-1] if house == house[_n-1] & dem == dem[_n-1]
{txt}(4 missing values generated)

{com}. rename cong congress
{res}{txt}
{com}. save "LeaderCVP_HouseSenate.dta", replace
{txt}{p 0 4 2}
(file {bf}
LeaderCVP_HouseSenate.dta{rm}
not found)
{p_end}
{p 0 4 2}
file {bf}
LeaderCVP_HouseSenate.dta{rm}
saved
{p_end}

{com}. restore
{txt}
{com}. drop if _merge == 3 & congress >= mincong
{txt}(187 observations deleted)

{com}. drop _merge mincong maxcong
{txt}
{com}. /*
> classify members as moderate:
> -compute first adjusted CVP for each member-party-chamber
> -compute median first adjusted CVP for each congress-party-chamber
> -if Dem is more conservative or Rep is more liberal than median, classify as a moderate member-Congress
> -compute share of moderate Congresses for each member
> -classify member as moderate if they are moderate for more than half of their congresses
> */
. egen member = group(icpsr dem house)
{txt}
{com}. egen mincong = min(congress), by(member)
{txt}
{com}. g temp = cvp if congress == mincong
{txt}(31,911 missing values generated)

{com}. egen firstcvp = mean(temp), by(member)
{txt}
{com}. drop temp mincong
{txt}
{com}. keep if congress >= 76 & congress <= 117
{txt}(19,517 observations deleted)

{com}. egen cong_chamber_party = group(congress house dem)
{txt}
{com}. egen medianfirst = median(firstcvp), by(cong_chamber_party)
{txt}
{com}. g moderate = 0
{txt}
{com}. replace moderate = 1 if firstcvp > medianfirst & dem == 1
{txt}(6,244 real changes made)

{com}. replace moderate = 1 if firstcvp < medianfirst & dem == 0
{txt}(5,069 real changes made)

{com}. egen meanmoderate = mean(moderate), by(member)
{txt}
{com}. drop moderate
{txt}
{com}. g moderate = meanmoderate > .5
{txt}
{com}. drop member firstcvp cong_chamber_party medianfirst meanmoderate
{txt}
{com}. *merge in leader CVP
. merge m:1 congress house dem using "LeaderCVP_HouseSenate.dta"
{res}
{txt}{col 5}Result{col 33}Number of obs
{col 5}{hline 41}
{col 5}Not matched{col 30}{res}               0
{txt}{col 5}Matched{col 30}{res}          22,713{txt}  (_merge==3)
{col 5}{hline 41}

{com}. drop _merge
{txt}
{com}. save "Member_CVP_Cleaned.dta", replace
{txt}{p 0 4 2}
(file {bf}
Member_CVP_Cleaned.dta{rm}
not found)
{p_end}
{p 0 4 2}
file {bf}
Member_CVP_Cleaned.dta{rm}
saved
{p_end}

{com}. 
. clear
{txt}
{com}. import delimited "HSall_members.csv"
{res}{txt}(encoding automatically selected: ISO-8859-1)
{res}{text}(22 vars, 50,485 obs)

{com}. drop if chamber == "President"
{txt}(127 observations deleted)

{com}. g house = chamber == "House"
{txt}
{com}. keep if congress >= 76 & congress <= 117
{txt}(27,344 observations deleted)

{com}. keep if party == 100 | party == 200
{txt}(75 observations deleted)

{com}. g dem = party == 100
{txt}
{com}. keep congress house icpsr bioname dem
{txt}
{com}. merge 1:1 congress house icpsr dem using "Member_CVP_Cleaned.dta"
{res}{txt}{p 0 7 2}
(variable
{bf:congress} was {bf:int}, now {bf:float} to accommodate using data's values)
{p_end}
{p 0 7 2}
(variable
{bf:icpsr} was {bf:long}, now {bf:double} to accommodate using data's values)
{p_end}

{col 5}Result{col 33}Number of obs
{col 5}{hline 41}
{col 5}Not matched{col 30}{res}             226
{txt}{col 9}from master{col 30}{res}             226{txt}  (_merge==1)
{col 9}from using{col 30}{res}               0{txt}  (_merge==2)

{col 5}Matched{col 30}{res}          22,713{txt}  (_merge==3)
{col 5}{hline 41}

{com}. keep if _merge == 3
{txt}(226 observations deleted)

{com}. drop _merge
{txt}
{com}. g majority = dem
{txt}
{com}. replace majority = 1 - dem if congress == 81 & house == 1
{txt}(441 real changes made)

{com}. replace majority = 1 - dem if congress == 83 & house == 1
{txt}(438 real changes made)

{com}. replace majority = 1 - dem if congress >= 104 & congress <= 109 & house == 1
{txt}(2,630 real changes made)

{com}. replace majority = 1 - dem if congress >= 112 & congress <= 115 & house == 1
{txt}(1,770 real changes made)

{com}. replace majority = 1 - dem if congress == 81 & house == 0
{txt}(105 real changes made)

{com}. replace majority = 1 - dem if congress == 83 & house == 0
{txt}(107 real changes made)

{com}. replace majority = 1 - dem if congress >= 104 & congress <= 109 & house == 0
{txt}(584 real changes made)

{com}. replace majority = 1 - dem if congress >= 112 & congress <= 115 & house == 0
{txt}(397 real changes made)

{com}. save "members_cleaned.dta", replace
{txt}{p 0 4 2}
(file {bf}
members_cleaned.dta{rm}
not found)
{p_end}
{p 0 4 2}
file {bf}
members_cleaned.dta{rm}
saved
{p_end}

{com}. 
. clear
{txt}
{com}. import delimited "HSall_votes.csv"
{res}{txt}(encoding automatically selected: ISO-8859-2)
{res}{text}(6 vars, 25,532,272 obs)

{com}. keep if congress >= 76 & congress <= 117
{txt}(8,178,958 observations deleted)

{com}. drop if cast_code == 0 | cast_code == 7 | cast_code == 8 | cast_code == 9
{txt}(1,218,038 observations deleted)

{com}. g yea = cast_code <= 3
{txt}
{com}. g house = chamber == "House" 
{txt}
{com}. drop cast_code prob
{txt}
{com}. merge m:1 icpsr congress house using "members_cleaned.dta"
{res}{txt}{p 0 7 2}
(variable
{bf:congress} was {bf:int}, now {bf:float} to accommodate using data's values)
{p_end}
{p 0 7 2}
(variable
{bf:icpsr} was {bf:long}, now {bf:double} to accommodate using data's values)
{p_end}

{col 5}Result{col 33}Number of obs
{col 5}{hline 41}
{col 5}Not matched{col 30}{res}         143,422
{txt}{col 9}from master{col 30}{res}         143,422{txt}  (_merge==1)
{col 9}from using{col 30}{res}               0{txt}  (_merge==2)

{col 5}Matched{col 30}{res}      15,991,854{txt}  (_merge==3)
{col 5}{hline 41}

{com}. keep if _merge == 3
{txt}(143,422 observations deleted)

{com}. drop _merge
{txt}
{com}. egen member_party_chamber = group(icpsr dem chamber)
{txt}
{com}. egen party_chamber = group(dem chamber)
{txt}
{com}. egen party_chamber_congress = group(dem chamber congress)
{txt}
{com}. egen bill = group(congress chamber rollnumber)
{txt}
{com}. g demyea = yea if dem == 1
{txt}(7,378,950 missing values generated)

{com}. g repyea = yea if dem == 0
{txt}(8,612,904 missing values generated)

{com}. egen meandemyea = mean(demyea), by(bill)
{txt}
{com}. egen meanrepyea = mean(repyea), by(bill)
{txt}(94 missing values generated)

{com}. *drop unanimous votes
. drop if meandemyea == 1 & meanrepyea == 1
{txt}(1,405,208 observations deleted)

{com}. drop if meandemyea == 0 & meanrepyea == 0
{txt}(9,288 observations deleted)

{com}. drop bill
{txt}
{com}. egen bill = group(congress chamber rollnumber)
{txt}
{com}. g conservative = yea
{txt}
{com}. replace conservative = 1 - yea if meandemyea > meanrepyea
{txt}(8,091,227 real changes made)

{com}. g withrepublicans = yea
{txt}
{com}. replace withrepublicans = 1 - yea if meanrepyea < .5
{txt}(5,669,710 real changes made)

{com}. g againstdemocrats = yea
{txt}
{com}. replace againstdemocrats = 1 - yea if meandemyea > .5
{txt}(9,276,117 real changes made)

{com}. drop *demyea *repyea chamber
{txt}
{com}. sort congress house bill icpsr 
{txt}
{com}. order congress house rollnumber icpsr dem majority bioname yea conservative withrepublicans againstdemocrats bill member_party_chamber party_chamber party_chamber_congress 
{txt}
{com}. save "rollcalls_prelim.dta", replace
{txt}{p 0 4 2}
(file {bf}
rollcalls_prelim.dta{rm}
not found)
{p_end}
{p 0 4 2}
file {bf}
rollcalls_prelim.dta{rm}
saved
{p_end}

{com}. keep bill conservative cvp
{txt}
{com}. save "votes_prelim.dta", replace
{txt}{p 0 4 2}
(file {bf}
votes_prelim.dta{rm}
not found)
{p_end}
{p 0 4 2}
file {bf}
votes_prelim.dta{rm}
saved
{p_end}

{com}. 
. clear
{txt}
{com}. postutil clear
{txt}
{com}. postfile Recodings bill recode using "Recodings.dta", replace
{txt}{p 0 4 2}
(file {bf}
Recodings.dta{rm}
not found)
{p_end}

{com}. use "votes_prelim.dta"
{txt}
{com}. sum bill

{txt}    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 8}bill {c |}{res} 14,577,358    29199.13    15199.04          1      54545
{txt}
{com}. local nbills = r(max)
{txt}
{com}. quietly {c -(}
500 15:12:01
1000 15:17:30
1500 15:23:02
2000 15:28:44
2500 15:34:32
3000 15:40:07
3500 15:45:33
4000 15:50:45
4500 15:56:02
5000 16:01:21
5500 16:06:43
6000 16:11:51
6500 16:17:08
7000 16:22:29
7500 16:27:40
8000 16:32:54
8500 16:38:11
9000 16:43:29
9500 16:48:43
10000 16:54:00
10500 16:59:17
11000 17:04:30
11500 17:09:47
12000 17:15:27
12500 17:21:00
13000 17:26:04
13500 17:31:26
14000 17:36:50
14500 17:42:11
15000 17:47:31
15500 17:52:27
16000 17:57:52
16500 18:01:28
17000 18:04:24
17500 18:07:21
18000 18:10:15
18500 18:13:09
19000 18:16:06
19500 18:19:02
20000 18:21:55
20500 18:24:48
21000 18:27:42
21500 18:30:37
22000 18:33:30
22500 18:36:27
23000 18:39:22
23500 18:42:15
24000 18:45:10
24500 18:48:06
25000 18:50:58
25500 18:53:53
26000 18:56:46
26500 18:59:40
27000 19:02:36
27500 19:05:29
28000 19:08:22
28500 19:11:15
29000 19:14:09
29500 19:17:01
30000 19:19:56
30500 19:22:50
31000 19:25:43
31500 19:28:36
32000 19:31:29
32500 19:34:24
33000 19:37:18
33500 19:40:14
34000 19:43:07
34500 19:45:59
35000 19:48:52
35500 19:51:47
36000 19:55:11
36500 19:58:03
37000 20:00:56
37500 20:03:49
38000 20:06:43
38500 20:09:36
39000 20:12:28
39500 20:15:22
40000 20:18:17
40500 20:21:13
41000 20:24:08
41500 20:27:01
42000 20:29:54
42500 20:32:49
43000 20:35:45
43500 20:38:37
44000 20:41:31
44500 20:44:24
45000 20:47:17
45500 20:50:10
46000 20:53:02
46500 20:55:56
47000 20:58:48
47500 21:01:40
48000 21:04:34
48500 21:07:27
49000 21:10:19
49500 21:13:11
50000 21:16:04
50500 21:18:56
51000 21:21:49
51500 21:24:41
52000 21:27:33
52500 21:30:27
53000 21:33:20
53500 21:36:18
54000 21:39:09
54500 21:42:02
{txt}
{com}. postclose Recodings
{txt}
{com}. clear 
{txt}
{com}. use "Recodings.dta"
{txt}
{com}. sum recode

{txt}    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 6}recode {c |}{res}      1,884           1           0          1          1
{txt}
{com}. disp r(N) " " `nbills' " " r(max)/`nbills'
{res}1884 54545 .00001833
{txt}
{com}. 
. *update leader CVP for Senate Republicans in 91st Congress
. clear
{txt}
{com}. import delimited "S091_rollcalls.csv"
{res}{txt}(encoding automatically selected: ISO-8859-1)
{text}(18 vars, 666 obs)

{com}. keep rollnumber date
{txt}
{com}. g day = date(date, "YMD")
{txt}
{com}. sort day 
{txt}
{com}. *Dirksen died on September 7, 1969 (day 3537)
. *Scott elected minority leader on September 24, 1969 (day 3554)
. g noleader = day >= 3537 & day < 3554
{txt}
{com}. g scott = day >= 3554
{txt}
{com}. g congress = 91
{txt}
{com}. g house = 0
{txt}
{com}. drop day date
{txt}
{com}. save "billdates.dta", replace
{txt}{p 0 4 2}
(file {bf}
billdates.dta{rm}
not found)
{p_end}
{p 0 4 2}
file {bf}
billdates.dta{rm}
saved
{p_end}

{com}. 
. clear
{txt}
{com}. use "rollcalls_prelim.dta"
{txt}
{com}. merge m:1 bill using "Recodings.dta"
{res}
{txt}{col 5}Result{col 33}Number of obs
{col 5}{hline 41}
{col 5}Not matched{col 30}{res}      14,194,020
{txt}{col 9}from master{col 30}{res}      14,194,020{txt}  (_merge==1)
{col 9}from using{col 30}{res}               0{txt}  (_merge==2)

{col 5}Matched{col 30}{res}         383,338{txt}  (_merge==3)
{col 5}{hline 41}

{com}. g reppartyvote = conservative
{txt}
{com}. replace conservative = 1 - conservative if recode == 1
{txt}(383,338 real changes made)

{com}. drop recode _merge
{txt}
{com}. merge m:1 congress house rollnumber using "billdates.dta"
{res}
{txt}{col 5}Result{col 33}Number of obs
{col 5}{hline 41}
{col 5}Not matched{col 30}{res}      14,526,728
{txt}{col 9}from master{col 30}{res}      14,526,649{txt}  (_merge==1)
{col 9}from using{col 30}{res}              79{txt}  (_merge==2)

{col 5}Matched{col 30}{res}          50,709{txt}  (_merge==3)
{col 5}{hline 41}

{com}. drop if _merge == 2
{txt}(79 observations deleted)

{com}. drop _merge
{txt}
{com}. replace noleader = 0 if dem == 1 & house == 0 & congress == 91
{txt}(470 real changes made)

{com}. replace scott = 0 if dem == 1 & house == 0 & congress == 91
{txt}(24,438 real changes made)

{com}. replace leader_cvp = . if noleader == 1
{txt}(361 real changes made, 361 to missing)

{com}. sum leader_cvp if dem == 0 & house == 0 & congress == 90

{txt}    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 2}leader_cvp {c |}{res}     17,879      .48585           0     .48585     .48585
{txt}
{com}. replace leader_cvp = r(mean) if dem == 0 & house == 0 & congress == 91 & scott + noleader == 0
{txt}(2,498 real changes made)

{com}. order congress house rollnumber icpsr dem majority bioname yea conservative reppartyvote withrepublicans againstdemocrats bill member_party_chamber party_chamber party_chamber_congress 
{txt}
{com}. save "CleanedRollCallData.dta", replace
{txt}{p 0 4 2}
file {bf}
CleanedRollCallData.dta{rm}
saved
{p_end}

{com}. 
. 
. *Figure 1
. clear
{txt}
{com}. use "CleanedRollCallData.dta"
{txt}
{com}. egen member_party_chamber_congress = group(icpsr dem house congress)
{res}{txt}
{com}. sort member_party_chamber_congress
{txt}
{com}. drop if member_party_chamber_congress == member_party_chamber_congress[_n-1]
{txt}(14,554,650 observations deleted)

{com}. drop if rollnumber == .
{txt}(0 observations deleted)

{com}. collapse (mean) cvp leader_cvp dem house congress, by(party_chamber_congress)
{res}{txt}
{com}. drop party_chamber_congress
{txt}
{com}. egen chamber_congress = group(house congress)
{txt}
{com}. reshape wide cvp leader_cvp, i(chamber_congress) j(dem)
{res}{txt}(j = 0 1)

Data{col 36}Long{col 43}->{col 48}Wide
{hline 77}
Number of observations     {res}         168   {txt}->   {res}84          
{txt}Number of variables        {res}           6   {txt}->   {res}7           
{txt}j variable (2 values)               {res}dem   {txt}->   (dropped)
xij variables:
                                    {res}cvp   {txt}->   {res}cvp0 cvp1
                             leader_cvp   {txt}->   {res}leader_cvp0 leader_cvp1
{txt}{hline 77}

{com}. g eyear = 1786 + cong*2
{txt}
{com}. g year = eyear + 1.5
{txt}
{com}. g reppre = cvp0 if cong <= 92
{txt}(50 missing values generated)

{com}. g reppost = cvp0 if cong >= 92
{txt}(32 missing values generated)

{com}. g dempre = cvp1 if cong <= 92
{txt}(50 missing values generated)

{com}. g dempost = cvp1 if cong >= 92
{txt}(32 missing values generated)

{com}. graph twoway (line cvp0 cvp1 year) (scatter leader_cvp0 leader_cvp1 year) (lfit reppre year) (lfit reppost year) (lfit dempre year) (lfit dempost year) if house == 1
{res}{txt}
{com}. gr_edit .legend.draw_view.setstyle, style(no)
{res}{txt}
{com}. gr_edit .style.editstyle margin(vsmall) boxstyle(shadestyle(color(white)) linestyle(color(white))) editcopy
{res}{txt}
{com}. gr_edit .yaxis1.style.editstyle majorstyle(gridstyle(linestyle(color(white)))) editcopy
{res}{txt}
{com}. gr_edit .xaxis1.style.editstyle majorstyle(gridstyle(linestyle(color(white)))) editcopy
{res}{txt}
{com}. gr_edit .yaxis1.title.text = {c -(}{c )-}
{res}{txt}
{com}. gr_edit .yaxis1.title.text.Arrpush CVP
{res}{txt}
{com}. gr_edit .xaxis1.title.text = {c -(}{c )-}
{res}{txt}
{com}. gr_edit .xaxis1.title.text.Arrpush Year
{res}{txt}
{com}. gr_edit .xaxis1.plotregion.xscale.curmax = 2021
{res}{txt}
{com}. gr_edit .plotregion1.plot1.style.editstyle line(color(red) width(thick)) editcopy
{res}{txt}
{com}. gr_edit .plotregion1.plot2.style.editstyle line(color(midblue) width(thick)) editcopy
{res}{txt}
{com}. gr_edit .plotregion1.plot3.style.editstyle marker(size(small) fillcolor(maroon) linestyle(color(maroon))) editcopy
{res}{txt}
{com}. gr_edit .plotregion1.plot4.style.editstyle marker(size(small) fillcolor(navy) linestyle(color(navy))) editcopy
{res}{txt}
{com}. gr_edit .plotregion1.plot5.style.editstyle line(color(cranberry) pattern(dash)) editcopy
{res}{txt}
{com}. gr_edit .plotregion1.plot6.style.editstyle line(color(cranberry) pattern(dash)) editcopy
{res}{txt}
{com}. gr_edit .plotregion1.plot7.style.editstyle line(color(blue) pattern(dash)) editcopy
{res}{txt}
{com}. gr_edit .plotregion1.plot8.style.editstyle line(color(blue) pattern(dash)) editcopy
{res}{txt}
{com}. gr_edit .title.style.editstyle color(black) editcopy
{res}{txt}
{com}. gr_edit .title.text = {c -(}{c )-}
{res}{txt}
{com}. gr_edit .title.text.Arrpush House
{res}{txt}
{com}. graph save "PolarizationHouse.gph", replace
{txt}{p 0 4 2}
(file {bf}
PolarizationHouse.gph{rm}
not found)
{p_end}
{res}{txt}file {bf:PolarizationHouse.gph} saved

{com}. graph twoway (line cvp0 cvp1 year) (scatter leader_cvp0 leader_cvp1 year) (lfit reppre year) (lfit reppost year) (lfit dempre year) (lfit dempost year) if house == 0
{res}{txt}
{com}. gr_edit .legend.draw_view.setstyle, style(no)
{res}{txt}
{com}. gr_edit .style.editstyle margin(vsmall) boxstyle(shadestyle(color(white)) linestyle(color(white))) editcopy
{res}{txt}
{com}. gr_edit .yaxis1.style.editstyle majorstyle(gridstyle(linestyle(color(white)))) editcopy
{res}{txt}
{com}. gr_edit .xaxis1.style.editstyle majorstyle(gridstyle(linestyle(color(white)))) editcopy
{res}{txt}
{com}. gr_edit .yaxis1.title.text = {c -(}{c )-}
{res}{txt}
{com}. gr_edit .yaxis1.title.text.Arrpush CVP
{res}{txt}
{com}. gr_edit .xaxis1.title.text = {c -(}{c )-}
{res}{txt}
{com}. gr_edit .xaxis1.title.text.Arrpush Year
{res}{txt}
{com}. gr_edit .xaxis1.plotregion.xscale.curmax = 2021
{res}{txt}
{com}. gr_edit .plotregion1.plot1.style.editstyle line(color(red) width(thick)) editcopy
{res}{txt}
{com}. gr_edit .plotregion1.plot2.style.editstyle line(color(midblue) width(thick)) editcopy
{res}{txt}
{com}. gr_edit .plotregion1.plot3.style.editstyle marker(size(small) fillcolor(maroon) linestyle(color(maroon))) editcopy
{res}{txt}
{com}. gr_edit .plotregion1.plot4.style.editstyle marker(size(small) fillcolor(navy) linestyle(color(navy))) editcopy
{res}{txt}
{com}. gr_edit .plotregion1.plot5.style.editstyle line(color(cranberry) pattern(dash)) editcopy
{res}{txt}
{com}. gr_edit .plotregion1.plot6.style.editstyle line(color(cranberry) pattern(dash)) editcopy
{res}{txt}
{com}. gr_edit .plotregion1.plot7.style.editstyle line(color(blue) pattern(dash)) editcopy
{res}{txt}
{com}. gr_edit .plotregion1.plot8.style.editstyle line(color(blue) pattern(dash)) editcopy
{res}{txt}
{com}. gr_edit .title.style.editstyle color(black) editcopy
{res}{txt}
{com}. gr_edit .title.text = {c -(}{c )-}
{res}{txt}
{com}. gr_edit .title.text.Arrpush Senate
{res}{txt}
{com}. graph save "PolarizationSenate.gph", replace
{txt}{p 0 4 2}
(file {bf}
PolarizationSenate.gph{rm}
not found)
{p_end}
{res}{txt}file {bf:PolarizationSenate.gph} saved

{com}. graph combine "PolarizationHouse.gph" "PolarizationSenate.gph", col(1)
{res}{txt}
{com}. gr_edit .style.editstyle margin(vsmall) boxstyle(shadestyle(color(white)) linestyle(color(white))) editcopy
{res}{txt}
{com}. gr_edit .style.editstyle declared_ysize(8) editcopy
{res}{txt}
{com}. graph export "Polarization.png", replace as(png)
{txt}{p 0 4 2}
(file {bf}
Polarization.png{rm}
not found)
{p_end}
{p 0 4 2}
file {bf}
Polarization.png{rm}
saved as
PNG
format
{p_end}

{com}. 
. 
. *Table 1
. clear
{txt}
{com}. use "CleanedRollCallData.dta"
{txt}
{com}. keep if congress >= 77 & congress <= 116
{txt}(587,769 observations deleted)

{com}. *correlations reported in footnote
. corr conservative reppartyvote withrepublicans againstdemocrats
{txt}(obs=13,989,589)

             {c |} conser~e reppar~e withre~s agains~s
{hline 13}{c +}{hline 36}
conservative {c |}{res}   1.0000
{txt}reppartyvote {c |}{res}   0.9453   1.0000
{txt}withrepubl~s {c |}{res}   0.5531   0.5731   1.0000
{txt}againstdem~s {c |}{res}   0.6853   0.6724   0.3015   1.0000

{txt}
{com}. g leader_cvp_dem = leader_cvp*dem
{txt}(361 missing values generated)

{com}. g leader_cvp_majority = leader_cvp*majority
{txt}(361 missing values generated)

{com}. g leader_cvp_house = leader_cvp*house
{txt}(361 missing values generated)

{com}. g leader_cvp_moderate = leader_cvp*moderate
{txt}(361 missing values generated)

{com}. 
. areg conservative leader_cvp, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}    .03895
{txt}Iteration 2:  Maximum absolute difference ={res}    .02857
{txt}Iteration 3:  Maximum absolute difference ={res}    .01893
{txt}Iteration 4:  Maximum absolute difference ={res}   .009356
{txt}Iteration 5:  Maximum absolute difference ={res}   .003386
{txt}Iteration 6:  Maximum absolute difference ={res}  .0008816
{txt}Iteration 7:  Maximum absolute difference ={res}  .0005758
{txt}Iteration 8:  Maximum absolute difference ={res}  .0006145
{txt}Iteration 9:  Maximum absolute difference ={res}  .0002503
{txt}Iteration 10: Maximum absolute difference ={res}  .0001303
{txt}Iteration 11: Maximum absolute difference ={res} .00009942
{txt}Iteration 12: Maximum absolute difference ={res} .00001004
{txt}Iteration 13: Maximum absolute difference ={res} 5.025e-06
{txt}Iteration 14: Maximum absolute difference ={res} 3.835e-06
{txt}Iteration 15: Maximum absolute difference ={res} 3.671e-06
{txt}Iteration 16: Maximum absolute difference ={res} 1.108e-06
{txt}Iteration 17: Maximum absolute difference ={res} 4.112e-07
{txt}Iteration 18: Maximum absolute difference ={res} 6.985e-08
{txt}Iteration 19: Maximum absolute difference ={res} 5.242e-09

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}    .05072
{txt}Iteration 2:  Maximum absolute difference ={res}     .0215
{txt}Iteration 3:  Maximum absolute difference ={res}    .01512
{txt}Iteration 4:  Maximum absolute difference ={res}   .007332
{txt}Iteration 5:  Maximum absolute difference ={res}   .005705
{txt}Iteration 6:  Maximum absolute difference ={res}   .005201
{txt}Iteration 7:  Maximum absolute difference ={res}   .002405
{txt}Iteration 8:  Maximum absolute difference ={res}  .0006931
{txt}Iteration 9:  Maximum absolute difference ={res}  .0001041
{txt}Iteration 10: Maximum absolute difference ={res} .00008679
{txt}Iteration 11: Maximum absolute difference ={res}  .0001124
{txt}Iteration 12: Maximum absolute difference ={res} .00002002
{txt}Iteration 13: Maximum absolute difference ={res} .00001074
{txt}Iteration 14: Maximum absolute difference ={res} 6.606e-06
{txt}Iteration 15: Maximum absolute difference ={res} 2.641e-06
{txt}Iteration 16: Maximum absolute difference ={res} 1.002e-06
{txt}Iteration 17: Maximum absolute difference ={res} 4.247e-07
{txt}Iteration 18: Maximum absolute difference ={res} 2.650e-08
{txt}Iteration 19: Maximum absolute difference ={res} 4.510e-09

{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 13:Number of obs}{col 66} = {res}{ralign 10:13,989,228}
{txt}{col 53}{lalign 13:Cluster comb.}{col 66} = {res}{ralign 10:3}
{txt}{col 1}Clusters per comb.:{col 53}{lalign 13:F({res:1}, {res:159})}{col 66} = {res}{ralign 10:25.33}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 6:160}{txt}{col 53}{lalign 13:Prob > F}{col 66} = {res}{ralign 10:0.0000}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 6:8,596}{txt}{col 53}{lalign 13:R-squared}{col 66} = {res}{ralign 10:0.5529}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 6:21,610}{txt}{col 53}{lalign 13:Adj R-squared}{col 66} = {res}{ralign 10:0.5511}
{txt}{col 53}{lalign 13:Root MSE}{col 66} = {res}{ralign 10:0.3334}

{txt}{ralign 78:(Std. err. adjusted for multiway clustering)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}conservative{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}leader_cvp {c |}{col 14}{res}{space 2} .3893818{col 26}{space 2} .0773733{col 37}{space 1}    5.03{col 46}{space 3}0.000{col 54}{space 4} .2365697{col 67}{space 3} .5421939
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .3770847{col 26}{space 2} .0149459{col 37}{space 1}   25.23{col 46}{space 3}0.000{col 54}{space 4} .3475665{col 67}{space 3} .4066029
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table1_conservative.txt", replace 2aster dec(3) sortvar(leader_next leader_cvp leader_prev)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table1_conservative.txt""':seeout}

{com}. areg conservative leader_next leader_cvp, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}    .03895
{txt}Iteration 2:  Maximum absolute difference ={res}    .02857
{txt}Iteration 3:  Maximum absolute difference ={res}    .01893
{txt}Iteration 4:  Maximum absolute difference ={res}   .009356
{txt}Iteration 5:  Maximum absolute difference ={res}   .003386
{txt}Iteration 6:  Maximum absolute difference ={res}  .0008816
{txt}Iteration 7:  Maximum absolute difference ={res}  .0005758
{txt}Iteration 8:  Maximum absolute difference ={res}  .0006145
{txt}Iteration 9:  Maximum absolute difference ={res}  .0002503
{txt}Iteration 10: Maximum absolute difference ={res}  .0001303
{txt}Iteration 11: Maximum absolute difference ={res} .00009942
{txt}Iteration 12: Maximum absolute difference ={res} .00001004
{txt}Iteration 13: Maximum absolute difference ={res} 5.025e-06
{txt}Iteration 14: Maximum absolute difference ={res} 3.835e-06
{txt}Iteration 15: Maximum absolute difference ={res} 3.671e-06
{txt}Iteration 16: Maximum absolute difference ={res} 1.108e-06
{txt}Iteration 17: Maximum absolute difference ={res} 4.112e-07
{txt}Iteration 18: Maximum absolute difference ={res} 6.985e-08
{txt}Iteration 19: Maximum absolute difference ={res} 5.242e-09

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}    .05072
{txt}Iteration 2:  Maximum absolute difference ={res}     .0215
{txt}Iteration 3:  Maximum absolute difference ={res}    .01512
{txt}Iteration 4:  Maximum absolute difference ={res}   .007332
{txt}Iteration 5:  Maximum absolute difference ={res}   .005705
{txt}Iteration 6:  Maximum absolute difference ={res}   .005201
{txt}Iteration 7:  Maximum absolute difference ={res}   .002405
{txt}Iteration 8:  Maximum absolute difference ={res}  .0007313
{txt}Iteration 9:  Maximum absolute difference ={res}  .0001041
{txt}Iteration 10: Maximum absolute difference ={res} .00008679
{txt}Iteration 11: Maximum absolute difference ={res}  .0001124
{txt}Iteration 12: Maximum absolute difference ={res} .00002002
{txt}Iteration 13: Maximum absolute difference ={res} .00001074
{txt}Iteration 14: Maximum absolute difference ={res} 6.606e-06
{txt}Iteration 15: Maximum absolute difference ={res} 2.641e-06
{txt}Iteration 16: Maximum absolute difference ={res} 1.023e-06
{txt}Iteration 17: Maximum absolute difference ={res} 4.247e-07
{txt}Iteration 18: Maximum absolute difference ={res} 3.087e-08
{txt}Iteration 19: Maximum absolute difference ={res} 8.370e-09

{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 13:Number of obs}{col 66} = {res}{ralign 10:13,989,228}
{txt}{col 53}{lalign 13:Cluster comb.}{col 66} = {res}{ralign 10:3}
{txt}{col 1}Clusters per comb.:{col 53}{lalign 13:F({res:2}, {res:159})}{col 66} = {res}{ralign 10:13.48}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 6:160}{txt}{col 53}{lalign 13:Prob > F}{col 66} = {res}{ralign 10:0.0000}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 6:8,596}{txt}{col 53}{lalign 13:R-squared}{col 66} = {res}{ralign 10:0.5529}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 6:21,610}{txt}{col 53}{lalign 13:Adj R-squared}{col 66} = {res}{ralign 10:0.5511}
{txt}{col 53}{lalign 13:Root MSE}{col 66} = {res}{ralign 10:0.3334}

{txt}{ralign 78:(Std. err. adjusted for multiway clustering)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}conservative{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}leader_next {c |}{col 14}{res}{space 2} .0441072{col 26}{space 2} .1114423{col 37}{space 1}    0.40{col 46}{space 3}0.693{col 54}{space 4} -.175991{col 67}{space 3} .2642053
{txt}{space 2}leader_cvp {c |}{col 14}{res}{space 2}  .360764{col 26}{space 2} .1129513{col 37}{space 1}    3.19{col 46}{space 3}0.002{col 54}{space 4} .1376856{col 67}{space 3} .5838424
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .3741148{col 26}{space 2} .0156937{col 37}{space 1}   23.84{col 46}{space 3}0.000{col 54}{space 4} .3431198{col 67}{space 3} .4051098
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table1_conservative.txt", append 2aster dec(3) sortvar(leader_next leader_cvp leader_prev)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table1_conservative.txt""':seeout}

{com}. areg conservative leader_next leader_cvp leader_prev, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}    .03895
{txt}Iteration 2:  Maximum absolute difference ={res}    .02857
{txt}Iteration 3:  Maximum absolute difference ={res}    .01893
{txt}Iteration 4:  Maximum absolute difference ={res}   .009356
{txt}Iteration 5:  Maximum absolute difference ={res}   .003386
{txt}Iteration 6:  Maximum absolute difference ={res}  .0008816
{txt}Iteration 7:  Maximum absolute difference ={res}  .0005758
{txt}Iteration 8:  Maximum absolute difference ={res}  .0006145
{txt}Iteration 9:  Maximum absolute difference ={res}  .0002503
{txt}Iteration 10: Maximum absolute difference ={res}  .0001303
{txt}Iteration 11: Maximum absolute difference ={res} .00009942
{txt}Iteration 12: Maximum absolute difference ={res} .00001004
{txt}Iteration 13: Maximum absolute difference ={res} 5.025e-06
{txt}Iteration 14: Maximum absolute difference ={res} 3.835e-06
{txt}Iteration 15: Maximum absolute difference ={res} 3.671e-06
{txt}Iteration 16: Maximum absolute difference ={res} 1.108e-06
{txt}Iteration 17: Maximum absolute difference ={res} 4.112e-07
{txt}Iteration 18: Maximum absolute difference ={res} 6.985e-08
{txt}Iteration 19: Maximum absolute difference ={res} 5.242e-09

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}    .05072
{txt}Iteration 2:  Maximum absolute difference ={res}     .0215
{txt}Iteration 3:  Maximum absolute difference ={res}    .01512
{txt}Iteration 4:  Maximum absolute difference ={res}   .008241
{txt}Iteration 5:  Maximum absolute difference ={res}   .005819
{txt}Iteration 6:  Maximum absolute difference ={res}   .006616
{txt}Iteration 7:  Maximum absolute difference ={res}   .002405
{txt}Iteration 8:  Maximum absolute difference ={res}  .0007313
{txt}Iteration 9:  Maximum absolute difference ={res}  .0001232
{txt}Iteration 10: Maximum absolute difference ={res} .00008679
{txt}Iteration 11: Maximum absolute difference ={res}  .0001124
{txt}Iteration 12: Maximum absolute difference ={res} .00002592
{txt}Iteration 13: Maximum absolute difference ={res} .00001074
{txt}Iteration 14: Maximum absolute difference ={res} 6.606e-06
{txt}Iteration 15: Maximum absolute difference ={res} 2.641e-06
{txt}Iteration 16: Maximum absolute difference ={res} 1.023e-06
{txt}Iteration 17: Maximum absolute difference ={res} 4.434e-07
{txt}Iteration 18: Maximum absolute difference ={res} 3.751e-08
{txt}Iteration 19: Maximum absolute difference ={res} 8.370e-09

{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 13:Number of obs}{col 66} = {res}{ralign 10:13,989,228}
{txt}{col 53}{lalign 13:Cluster comb.}{col 66} = {res}{ralign 10:3}
{txt}{col 1}Clusters per comb.:{col 53}{lalign 13:F({res:3}, {res:159})}{col 66} = {res}{ralign 10:17.24}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 6:160}{txt}{col 53}{lalign 13:Prob > F}{col 66} = {res}{ralign 10:0.0000}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 6:8,596}{txt}{col 53}{lalign 13:R-squared}{col 66} = {res}{ralign 10:0.5534}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 6:21,610}{txt}{col 53}{lalign 13:Adj R-squared}{col 66} = {res}{ralign 10:0.5516}
{txt}{col 53}{lalign 13:Root MSE}{col 66} = {res}{ralign 10:0.3332}

{txt}{ralign 78:(Std. err. adjusted for multiway clustering)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}conservative{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}leader_next {c |}{col 14}{res}{space 2} .0539272{col 26}{space 2} .1149792{col 37}{space 1}    0.47{col 46}{space 3}0.640{col 54}{space 4}-.1731562{col 67}{space 3} .2810107
{txt}{space 2}leader_cvp {c |}{col 14}{res}{space 2}-.0581575{col 26}{space 2} .1313159{col 37}{space 1}   -0.44{col 46}{space 3}0.658{col 54}{space 4} -.317506{col 67}{space 3}  .201191
{txt}{space 1}leader_prev {c |}{col 14}{res}{space 2} .5808103{col 26}{space 2} .1149839{col 37}{space 1}    5.05{col 46}{space 3}0.000{col 54}{space 4} .3537176{col 67}{space 3}  .807903
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .3416279{col 26}{space 2} .0166077{col 37}{space 1}   20.57{col 46}{space 3}0.000{col 54}{space 4} .3088277{col 67}{space 3}  .374428
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table1_conservative.txt", append 2aster dec(3) sortvar(leader_next leader_cvp leader_prev)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table1_conservative.txt""':seeout}

{com}. areg conservative leader_cvp leader_cvp_house, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}    .03895
{txt}Iteration 2:  Maximum absolute difference ={res}    .02857
{txt}Iteration 3:  Maximum absolute difference ={res}    .01893
{txt}Iteration 4:  Maximum absolute difference ={res}   .009356
{txt}Iteration 5:  Maximum absolute difference ={res}   .003386
{txt}Iteration 6:  Maximum absolute difference ={res}  .0008816
{txt}Iteration 7:  Maximum absolute difference ={res}  .0005758
{txt}Iteration 8:  Maximum absolute difference ={res}  .0006145
{txt}Iteration 9:  Maximum absolute difference ={res}  .0002503
{txt}Iteration 10: Maximum absolute difference ={res}  .0001303
{txt}Iteration 11: Maximum absolute difference ={res} .00009942
{txt}Iteration 12: Maximum absolute difference ={res} .00001004
{txt}Iteration 13: Maximum absolute difference ={res} 5.025e-06
{txt}Iteration 14: Maximum absolute difference ={res} 3.835e-06
{txt}Iteration 15: Maximum absolute difference ={res} 3.671e-06
{txt}Iteration 16: Maximum absolute difference ={res} 1.108e-06
{txt}Iteration 17: Maximum absolute difference ={res} 4.112e-07
{txt}Iteration 18: Maximum absolute difference ={res} 6.985e-08
{txt}Iteration 19: Maximum absolute difference ={res} 5.242e-09

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}    .05072
{txt}Iteration 2:  Maximum absolute difference ={res}     .0215
{txt}Iteration 3:  Maximum absolute difference ={res}    .01512
{txt}Iteration 4:  Maximum absolute difference ={res}   .007332
{txt}Iteration 5:  Maximum absolute difference ={res}   .005705
{txt}Iteration 6:  Maximum absolute difference ={res}   .005201
{txt}Iteration 7:  Maximum absolute difference ={res}   .002405
{txt}Iteration 8:  Maximum absolute difference ={res}  .0006931
{txt}Iteration 9:  Maximum absolute difference ={res}  .0001041
{txt}Iteration 10: Maximum absolute difference ={res} .00008679
{txt}Iteration 11: Maximum absolute difference ={res}  .0001124
{txt}Iteration 12: Maximum absolute difference ={res} .00002002
{txt}Iteration 13: Maximum absolute difference ={res} .00001074
{txt}Iteration 14: Maximum absolute difference ={res} 6.606e-06
{txt}Iteration 15: Maximum absolute difference ={res} 2.641e-06
{txt}Iteration 16: Maximum absolute difference ={res} 1.002e-06
{txt}Iteration 17: Maximum absolute difference ={res} 4.247e-07
{txt}Iteration 18: Maximum absolute difference ={res} 2.650e-08
{txt}Iteration 19: Maximum absolute difference ={res} 4.510e-09

{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 13:Number of obs}{col 66} = {res}{ralign 10:13,989,228}
{txt}{col 53}{lalign 13:Cluster comb.}{col 66} = {res}{ralign 10:3}
{txt}{col 1}Clusters per comb.:{col 53}{lalign 13:F({res:2}, {res:159})}{col 66} = {res}{ralign 10:14.05}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 6:160}{txt}{col 53}{lalign 13:Prob > F}{col 66} = {res}{ralign 10:0.0000}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 6:8,596}{txt}{col 53}{lalign 13:R-squared}{col 66} = {res}{ralign 10:0.5530}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 6:21,610}{txt}{col 53}{lalign 13:Adj R-squared}{col 66} = {res}{ralign 10:0.5512}
{txt}{col 53}{lalign 13:Root MSE}{col 66} = {res}{ralign 10:0.3333}

{txt}{ralign 82:(Std. err. adjusted for multiway clustering)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}    conservative{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}leader_cvp {c |}{col 18}{res}{space 2} .1611693{col 30}{space 2} .0626456{col 41}{space 1}    2.57{col 50}{space 3}0.011{col 58}{space 4} .0374445{col 71}{space 3} .2848942
{txt}leader_cvp_house {c |}{col 18}{res}{space 2} .4434923{col 30}{space 2} .1447104{col 41}{space 1}    3.06{col 50}{space 3}0.003{col 58}{space 4} .1576898{col 71}{space 3} .7292947
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .3372858{col 30}{space 2} .0246593{col 41}{space 1}   13.68{col 50}{space 3}0.000{col 58}{space 4} .2885838{col 71}{space 3} .3859879
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table1_conservative.txt", append 2aster dec(3) sortvar(leader_next leader_cvp leader_prev)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table1_conservative.txt""':seeout}

{com}. areg conservative leader_cvp leader_cvp_dem, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}    .03895
{txt}Iteration 2:  Maximum absolute difference ={res}    .02857
{txt}Iteration 3:  Maximum absolute difference ={res}    .01893
{txt}Iteration 4:  Maximum absolute difference ={res}   .009356
{txt}Iteration 5:  Maximum absolute difference ={res}   .003386
{txt}Iteration 6:  Maximum absolute difference ={res}  .0008816
{txt}Iteration 7:  Maximum absolute difference ={res}  .0005758
{txt}Iteration 8:  Maximum absolute difference ={res}  .0006145
{txt}Iteration 9:  Maximum absolute difference ={res}  .0002503
{txt}Iteration 10: Maximum absolute difference ={res}  .0001303
{txt}Iteration 11: Maximum absolute difference ={res} .00009942
{txt}Iteration 12: Maximum absolute difference ={res} .00001004
{txt}Iteration 13: Maximum absolute difference ={res} 5.025e-06
{txt}Iteration 14: Maximum absolute difference ={res} 3.835e-06
{txt}Iteration 15: Maximum absolute difference ={res} 3.671e-06
{txt}Iteration 16: Maximum absolute difference ={res} 1.108e-06
{txt}Iteration 17: Maximum absolute difference ={res} 4.112e-07
{txt}Iteration 18: Maximum absolute difference ={res} 6.985e-08
{txt}Iteration 19: Maximum absolute difference ={res} 5.242e-09

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}    .05072
{txt}Iteration 2:  Maximum absolute difference ={res}     .0215
{txt}Iteration 3:  Maximum absolute difference ={res}    .01512
{txt}Iteration 4:  Maximum absolute difference ={res}   .007332
{txt}Iteration 5:  Maximum absolute difference ={res}   .005705
{txt}Iteration 6:  Maximum absolute difference ={res}   .005201
{txt}Iteration 7:  Maximum absolute difference ={res}   .002405
{txt}Iteration 8:  Maximum absolute difference ={res}   .001053
{txt}Iteration 9:  Maximum absolute difference ={res}  .0001041
{txt}Iteration 10: Maximum absolute difference ={res} .00008679
{txt}Iteration 11: Maximum absolute difference ={res}  .0001124
{txt}Iteration 12: Maximum absolute difference ={res} .00002002
{txt}Iteration 13: Maximum absolute difference ={res} .00001074
{txt}Iteration 14: Maximum absolute difference ={res} 6.606e-06
{txt}Iteration 15: Maximum absolute difference ={res} 2.641e-06
{txt}Iteration 16: Maximum absolute difference ={res} 1.002e-06
{txt}Iteration 17: Maximum absolute difference ={res} 4.247e-07
{txt}Iteration 18: Maximum absolute difference ={res} 2.650e-08
{txt}Iteration 19: Maximum absolute difference ={res} 4.510e-09

{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 13:Number of obs}{col 66} = {res}{ralign 10:13,989,228}
{txt}{col 53}{lalign 13:Cluster comb.}{col 66} = {res}{ralign 10:3}
{txt}{col 1}Clusters per comb.:{col 53}{lalign 13:F({res:2}, {res:159})}{col 66} = {res}{ralign 10:15.63}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 6:160}{txt}{col 53}{lalign 13:Prob > F}{col 66} = {res}{ralign 10:0.0000}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 6:8,596}{txt}{col 53}{lalign 13:R-squared}{col 66} = {res}{ralign 10:0.5529}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 6:21,610}{txt}{col 53}{lalign 13:Adj R-squared}{col 66} = {res}{ralign 10:0.5511}
{txt}{col 53}{lalign 13:Root MSE}{col 66} = {res}{ralign 10:0.3334}

{txt}{ralign 80:(Std. err. adjusted for multiway clustering)}
{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}  conservative{col 16}{c |} Coefficient{col 28}  std. err.{col 40}      t{col 48}   P>|t|{col 56}     [95% con{col 69}f. interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}leader_cvp {c |}{col 16}{res}{space 2} .4446362{col 28}{space 2} .0849708{col 39}{space 1}    5.23{col 48}{space 3}0.000{col 56}{space 4} .2768192{col 69}{space 3} .6124531
{txt}leader_cvp_dem {c |}{col 16}{res}{space 2}-.1501701{col 28}{space 2}  .185264{col 39}{space 1}   -0.81{col 48}{space 3}0.419{col 56}{space 4}-.5160658{col 69}{space 3} .2157256
{txt}{space 9}_cons {c |}{col 16}{res}{space 2} .3595549{col 28}{space 2} .0219547{col 39}{space 1}   16.38{col 48}{space 3}0.000{col 56}{space 4} .3161945{col 69}{space 3} .4029153
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table1_conservative.txt", append 2aster dec(3) sortvar(leader_next leader_cvp leader_prev)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table1_conservative.txt""':seeout}

{com}. areg conservative leader_cvp leader_cvp_majority, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}    .03895
{txt}Iteration 2:  Maximum absolute difference ={res}    .02857
{txt}Iteration 3:  Maximum absolute difference ={res}    .01893
{txt}Iteration 4:  Maximum absolute difference ={res}   .009356
{txt}Iteration 5:  Maximum absolute difference ={res}   .003386
{txt}Iteration 6:  Maximum absolute difference ={res}  .0008816
{txt}Iteration 7:  Maximum absolute difference ={res}  .0005758
{txt}Iteration 8:  Maximum absolute difference ={res}  .0006145
{txt}Iteration 9:  Maximum absolute difference ={res}  .0002503
{txt}Iteration 10: Maximum absolute difference ={res}  .0001303
{txt}Iteration 11: Maximum absolute difference ={res} .00009942
{txt}Iteration 12: Maximum absolute difference ={res} .00001004
{txt}Iteration 13: Maximum absolute difference ={res} 5.025e-06
{txt}Iteration 14: Maximum absolute difference ={res} 3.835e-06
{txt}Iteration 15: Maximum absolute difference ={res} 3.671e-06
{txt}Iteration 16: Maximum absolute difference ={res} 1.108e-06
{txt}Iteration 17: Maximum absolute difference ={res} 4.112e-07
{txt}Iteration 18: Maximum absolute difference ={res} 6.985e-08
{txt}Iteration 19: Maximum absolute difference ={res} 5.242e-09

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}     .1015
{txt}Iteration 2:  Maximum absolute difference ={res}    .05568
{txt}Iteration 3:  Maximum absolute difference ={res}    .05893
{txt}Iteration 4:  Maximum absolute difference ={res}    .02669
{txt}Iteration 5:  Maximum absolute difference ={res}    .05127
{txt}Iteration 6:  Maximum absolute difference ={res}    .02269
{txt}Iteration 7:  Maximum absolute difference ={res}   .007504
{txt}Iteration 8:  Maximum absolute difference ={res}   .004196
{txt}Iteration 9:  Maximum absolute difference ={res}   .001672
{txt}Iteration 10: Maximum absolute difference ={res}   .001032
{txt}Iteration 11: Maximum absolute difference ={res}  .0004369
{txt}Iteration 12: Maximum absolute difference ={res}  .0003134
{txt}Iteration 13: Maximum absolute difference ={res}  .0002368
{txt}Iteration 14: Maximum absolute difference ={res}  .0000242
{txt}Iteration 15: Maximum absolute difference ={res} 4.047e-06
{txt}Iteration 16: Maximum absolute difference ={res} 1.002e-06
{txt}Iteration 17: Maximum absolute difference ={res} 4.247e-07
{txt}Iteration 18: Maximum absolute difference ={res} 2.941e-08
{txt}Iteration 19: Maximum absolute difference ={res} 4.510e-09

{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 13:Number of obs}{col 66} = {res}{ralign 10:13,989,228}
{txt}{col 53}{lalign 13:Cluster comb.}{col 66} = {res}{ralign 10:3}
{txt}{col 1}Clusters per comb.:{col 53}{lalign 13:F({res:2}, {res:159})}{col 66} = {res}{ralign 10:13.22}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 6:160}{txt}{col 53}{lalign 13:Prob > F}{col 66} = {res}{ralign 10:0.0000}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 6:8,596}{txt}{col 53}{lalign 13:R-squared}{col 66} = {res}{ralign 10:0.5529}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 6:21,610}{txt}{col 53}{lalign 13:Adj R-squared}{col 66} = {res}{ralign 10:0.5511}
{txt}{col 53}{lalign 13:Root MSE}{col 66} = {res}{ralign 10:0.3334}

{txt}{ralign 85:(Std. err. adjusted for multiway clustering)}
{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}       conservative{col 21}{c |} Coefficient{col 33}  std. err.{col 45}      t{col 53}   P>|t|{col 61}     [95% con{col 74}f. interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}leader_cvp {c |}{col 21}{res}{space 2} .3960603{col 33}{space 2} .0823706{col 44}{space 1}    4.81{col 53}{space 3}0.000{col 61}{space 4} .2333786{col 74}{space 3} .5587419
{txt}leader_cvp_majority {c |}{col 21}{res}{space 2}-.0139546{col 33}{space 2} .0333624{col 44}{space 1}   -0.42{col 53}{space 3}0.676{col 61}{space 4}-.0798452{col 74}{space 3}  .051936
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} .3769678{col 33}{space 2} .0149096{col 44}{space 1}   25.28{col 53}{space 3}0.000{col 61}{space 4} .3475213{col 74}{space 3} .4064142
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table1_conservative.txt", append 2aster dec(3) sortvar(leader_next leader_cvp leader_prev)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table1_conservative.txt""':seeout}

{com}. areg conservative leader_cvp leader_cvp_moderate, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}    .03895
{txt}Iteration 2:  Maximum absolute difference ={res}    .02857
{txt}Iteration 3:  Maximum absolute difference ={res}    .01893
{txt}Iteration 4:  Maximum absolute difference ={res}   .009356
{txt}Iteration 5:  Maximum absolute difference ={res}   .003386
{txt}Iteration 6:  Maximum absolute difference ={res}  .0008816
{txt}Iteration 7:  Maximum absolute difference ={res}  .0005758
{txt}Iteration 8:  Maximum absolute difference ={res}  .0006145
{txt}Iteration 9:  Maximum absolute difference ={res}  .0002503
{txt}Iteration 10: Maximum absolute difference ={res}  .0001303
{txt}Iteration 11: Maximum absolute difference ={res} .00009942
{txt}Iteration 12: Maximum absolute difference ={res} .00001004
{txt}Iteration 13: Maximum absolute difference ={res} 5.025e-06
{txt}Iteration 14: Maximum absolute difference ={res} 3.835e-06
{txt}Iteration 15: Maximum absolute difference ={res} 3.671e-06
{txt}Iteration 16: Maximum absolute difference ={res} 1.108e-06
{txt}Iteration 17: Maximum absolute difference ={res} 4.112e-07
{txt}Iteration 18: Maximum absolute difference ={res} 6.985e-08
{txt}Iteration 19: Maximum absolute difference ={res} 5.242e-09

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}    .05072
{txt}Iteration 2:  Maximum absolute difference ={res}     .0215
{txt}Iteration 3:  Maximum absolute difference ={res}    .01512
{txt}Iteration 4:  Maximum absolute difference ={res}   .007332
{txt}Iteration 5:  Maximum absolute difference ={res}   .005705
{txt}Iteration 6:  Maximum absolute difference ={res}   .005201
{txt}Iteration 7:  Maximum absolute difference ={res}   .002405
{txt}Iteration 8:  Maximum absolute difference ={res}  .0006931
{txt}Iteration 9:  Maximum absolute difference ={res}  .0001041
{txt}Iteration 10: Maximum absolute difference ={res}  .0001422
{txt}Iteration 11: Maximum absolute difference ={res}  .0001124
{txt}Iteration 12: Maximum absolute difference ={res} .00002002
{txt}Iteration 13: Maximum absolute difference ={res} .00001074
{txt}Iteration 14: Maximum absolute difference ={res} 6.606e-06
{txt}Iteration 15: Maximum absolute difference ={res} 2.641e-06
{txt}Iteration 16: Maximum absolute difference ={res} 1.002e-06
{txt}Iteration 17: Maximum absolute difference ={res} 4.247e-07
{txt}Iteration 18: Maximum absolute difference ={res} 2.650e-08
{txt}Iteration 19: Maximum absolute difference ={res} 4.510e-09

{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 13:Number of obs}{col 66} = {res}{ralign 10:13,989,228}
{txt}{col 53}{lalign 13:Cluster comb.}{col 66} = {res}{ralign 10:3}
{txt}{col 1}Clusters per comb.:{col 53}{lalign 13:F({res:2}, {res:159})}{col 66} = {res}{ralign 10:14.30}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 6:160}{txt}{col 53}{lalign 13:Prob > F}{col 66} = {res}{ralign 10:0.0000}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 6:8,596}{txt}{col 53}{lalign 13:R-squared}{col 66} = {res}{ralign 10:0.5530}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 6:21,610}{txt}{col 53}{lalign 13:Adj R-squared}{col 66} = {res}{ralign 10:0.5511}
{txt}{col 53}{lalign 13:Root MSE}{col 66} = {res}{ralign 10:0.3334}

{txt}{ralign 85:(Std. err. adjusted for multiway clustering)}
{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}       conservative{col 21}{c |} Coefficient{col 33}  std. err.{col 45}      t{col 53}   P>|t|{col 61}     [95% con{col 74}f. interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}leader_cvp {c |}{col 21}{res}{space 2} .3026316{col 33}{space 2} .0822959{col 44}{space 1}    3.68{col 53}{space 3}0.000{col 61}{space 4} .1400975{col 74}{space 3} .4651658
{txt}leader_cvp_moderate {c |}{col 21}{res}{space 2} .1705866{col 33}{space 2} .0734436{col 44}{space 1}    2.32{col 53}{space 3}0.021{col 61}{space 4} .0255357{col 74}{space 3} .3156374
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} .3777875{col 33}{space 2} .0149156{col 44}{space 1}   25.33{col 53}{space 3}0.000{col 61}{space 4} .3483292{col 74}{space 3} .4072458
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table1_conservative.txt", append 2aster dec(3) sortvar(leader_next leader_cvp leader_prev)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table1_conservative.txt""':seeout}

{com}. 
. areg reppartyvote leader_cvp, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}     .0374
{txt}Iteration 2:  Maximum absolute difference ={res}    .02544
{txt}Iteration 3:  Maximum absolute difference ={res}    .01871
{txt}Iteration 4:  Maximum absolute difference ={res}    .00764
{txt}Iteration 5:  Maximum absolute difference ={res}   .003482
{txt}Iteration 6:  Maximum absolute difference ={res}   .003424
{txt}Iteration 7:  Maximum absolute difference ={res}    .00296
{txt}Iteration 8:  Maximum absolute difference ={res}     .0017
{txt}Iteration 9:  Maximum absolute difference ={res}   .000648
{txt}Iteration 10: Maximum absolute difference ={res}   .000247
{txt}Iteration 11: Maximum absolute difference ={res}  .0001668
{txt}Iteration 12: Maximum absolute difference ={res}    .00003
{txt}Iteration 13: Maximum absolute difference ={res} .00004226
{txt}Iteration 14: Maximum absolute difference ={res} .00001391
{txt}Iteration 15: Maximum absolute difference ={res} 6.269e-06
{txt}Iteration 16: Maximum absolute difference ={res} 1.255e-06
{txt}Iteration 17: Maximum absolute difference ={res} 1.356e-07
{txt}Iteration 18: Maximum absolute difference ={res} 2.877e-08
{txt}Iteration 19: Maximum absolute difference ={res} 5.191e-09

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}    .05072
{txt}Iteration 2:  Maximum absolute difference ={res}     .0215
{txt}Iteration 3:  Maximum absolute difference ={res}    .01512
{txt}Iteration 4:  Maximum absolute difference ={res}   .007332
{txt}Iteration 5:  Maximum absolute difference ={res}   .005705
{txt}Iteration 6:  Maximum absolute difference ={res}   .005201
{txt}Iteration 7:  Maximum absolute difference ={res}   .002405
{txt}Iteration 8:  Maximum absolute difference ={res}  .0006931
{txt}Iteration 9:  Maximum absolute difference ={res}  .0001041
{txt}Iteration 10: Maximum absolute difference ={res} .00008679
{txt}Iteration 11: Maximum absolute difference ={res}  .0001124
{txt}Iteration 12: Maximum absolute difference ={res} .00002002
{txt}Iteration 13: Maximum absolute difference ={res} .00001074
{txt}Iteration 14: Maximum absolute difference ={res} 6.606e-06
{txt}Iteration 15: Maximum absolute difference ={res} 2.641e-06
{txt}Iteration 16: Maximum absolute difference ={res} 1.002e-06
{txt}Iteration 17: Maximum absolute difference ={res} 4.247e-07
{txt}Iteration 18: Maximum absolute difference ={res} 2.650e-08
{txt}Iteration 19: Maximum absolute difference ={res} 4.510e-09

{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 13:Number of obs}{col 66} = {res}{ralign 10:13,989,228}
{txt}{col 53}{lalign 13:Cluster comb.}{col 66} = {res}{ralign 10:3}
{txt}{col 1}Clusters per comb.:{col 53}{lalign 13:F({res:1}, {res:159})}{col 66} = {res}{ralign 10:25.98}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 6:160}{txt}{col 53}{lalign 13:Prob > F}{col 66} = {res}{ralign 10:0.0000}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 6:8,596}{txt}{col 53}{lalign 13:R-squared}{col 66} = {res}{ralign 10:0.5503}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 6:21,610}{txt}{col 53}{lalign 13:Adj R-squared}{col 66} = {res}{ralign 10:0.5484}
{txt}{col 53}{lalign 13:Root MSE}{col 66} = {res}{ralign 10:0.3348}

{txt}{ralign 78:(Std. err. adjusted for multiway clustering)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}reppartyvote{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}leader_cvp {c |}{col 14}{res}{space 2} .3850429{col 26}{space 2} .0755415{col 37}{space 1}    5.10{col 46}{space 3}0.000{col 54}{space 4} .2358487{col 67}{space 3}  .534237
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .3850273{col 26}{space 2}  .014598{col 37}{space 1}   26.38{col 46}{space 3}0.000{col 54}{space 4} .3561963{col 67}{space 3} .4138582
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table1_republicandirection.txt", replace 2aster dec(3) sortvar(leader_next leader_cvp leader_prev)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table1_republicandirection.txt""':seeout}

{com}. areg reppartyvote leader_next leader_cvp, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}     .0374
{txt}Iteration 2:  Maximum absolute difference ={res}    .02544
{txt}Iteration 3:  Maximum absolute difference ={res}    .01871
{txt}Iteration 4:  Maximum absolute difference ={res}    .00764
{txt}Iteration 5:  Maximum absolute difference ={res}   .003482
{txt}Iteration 6:  Maximum absolute difference ={res}   .003424
{txt}Iteration 7:  Maximum absolute difference ={res}    .00296
{txt}Iteration 8:  Maximum absolute difference ={res}     .0017
{txt}Iteration 9:  Maximum absolute difference ={res}   .000648
{txt}Iteration 10: Maximum absolute difference ={res}   .000247
{txt}Iteration 11: Maximum absolute difference ={res}  .0001668
{txt}Iteration 12: Maximum absolute difference ={res}    .00003
{txt}Iteration 13: Maximum absolute difference ={res} .00004226
{txt}Iteration 14: Maximum absolute difference ={res} .00001391
{txt}Iteration 15: Maximum absolute difference ={res} 6.269e-06
{txt}Iteration 16: Maximum absolute difference ={res} 1.255e-06
{txt}Iteration 17: Maximum absolute difference ={res} 1.356e-07
{txt}Iteration 18: Maximum absolute difference ={res} 2.877e-08
{txt}Iteration 19: Maximum absolute difference ={res} 5.191e-09

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}    .05072
{txt}Iteration 2:  Maximum absolute difference ={res}     .0215
{txt}Iteration 3:  Maximum absolute difference ={res}    .01512
{txt}Iteration 4:  Maximum absolute difference ={res}   .007332
{txt}Iteration 5:  Maximum absolute difference ={res}   .005705
{txt}Iteration 6:  Maximum absolute difference ={res}   .005201
{txt}Iteration 7:  Maximum absolute difference ={res}   .002405
{txt}Iteration 8:  Maximum absolute difference ={res}  .0007313
{txt}Iteration 9:  Maximum absolute difference ={res}  .0001041
{txt}Iteration 10: Maximum absolute difference ={res} .00008679
{txt}Iteration 11: Maximum absolute difference ={res}  .0001124
{txt}Iteration 12: Maximum absolute difference ={res} .00002002
{txt}Iteration 13: Maximum absolute difference ={res} .00001074
{txt}Iteration 14: Maximum absolute difference ={res} 6.606e-06
{txt}Iteration 15: Maximum absolute difference ={res} 2.641e-06
{txt}Iteration 16: Maximum absolute difference ={res} 1.023e-06
{txt}Iteration 17: Maximum absolute difference ={res} 4.247e-07
{txt}Iteration 18: Maximum absolute difference ={res} 3.087e-08
{txt}Iteration 19: Maximum absolute difference ={res} 8.370e-09

{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 13:Number of obs}{col 66} = {res}{ralign 10:13,989,228}
{txt}{col 53}{lalign 13:Cluster comb.}{col 66} = {res}{ralign 10:3}
{txt}{col 1}Clusters per comb.:{col 53}{lalign 13:F({res:2}, {res:159})}{col 66} = {res}{ralign 10:13.72}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 6:160}{txt}{col 53}{lalign 13:Prob > F}{col 66} = {res}{ralign 10:0.0000}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 6:8,596}{txt}{col 53}{lalign 13:R-squared}{col 66} = {res}{ralign 10:0.5503}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 6:21,610}{txt}{col 53}{lalign 13:Adj R-squared}{col 66} = {res}{ralign 10:0.5484}
{txt}{col 53}{lalign 13:Root MSE}{col 66} = {res}{ralign 10:0.3348}

{txt}{ralign 78:(Std. err. adjusted for multiway clustering)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}reppartyvote{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}leader_next {c |}{col 14}{res}{space 2} .0395158{col 26}{space 2} .1078009{col 37}{space 1}    0.37{col 46}{space 3}0.714{col 54}{space 4}-.1733905{col 67}{space 3} .2524222
{txt}{space 2}leader_cvp {c |}{col 14}{res}{space 2}  .359404{col 26}{space 2} .1094811{col 37}{space 1}    3.28{col 46}{space 3}0.001{col 54}{space 4} .1431792{col 67}{space 3} .5756289
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .3823665{col 26}{space 2} .0153657{col 37}{space 1}   24.88{col 46}{space 3}0.000{col 54}{space 4} .3520194{col 67}{space 3} .4127136
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table1_republicandirection.txt", append 2aster dec(3) sortvar(leader_next leader_cvp leader_prev)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table1_republicandirection.txt""':seeout}

{com}. areg reppartyvote leader_next leader_cvp leader_prev, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}     .0374
{txt}Iteration 2:  Maximum absolute difference ={res}    .02544
{txt}Iteration 3:  Maximum absolute difference ={res}    .01871
{txt}Iteration 4:  Maximum absolute difference ={res}    .00764
{txt}Iteration 5:  Maximum absolute difference ={res}   .003482
{txt}Iteration 6:  Maximum absolute difference ={res}   .003424
{txt}Iteration 7:  Maximum absolute difference ={res}    .00296
{txt}Iteration 8:  Maximum absolute difference ={res}     .0017
{txt}Iteration 9:  Maximum absolute difference ={res}   .000648
{txt}Iteration 10: Maximum absolute difference ={res}   .000247
{txt}Iteration 11: Maximum absolute difference ={res}  .0001668
{txt}Iteration 12: Maximum absolute difference ={res}    .00003
{txt}Iteration 13: Maximum absolute difference ={res} .00004226
{txt}Iteration 14: Maximum absolute difference ={res} .00001391
{txt}Iteration 15: Maximum absolute difference ={res} 6.269e-06
{txt}Iteration 16: Maximum absolute difference ={res} 1.255e-06
{txt}Iteration 17: Maximum absolute difference ={res} 1.356e-07
{txt}Iteration 18: Maximum absolute difference ={res} 2.877e-08
{txt}Iteration 19: Maximum absolute difference ={res} 5.191e-09

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}    .05072
{txt}Iteration 2:  Maximum absolute difference ={res}     .0215
{txt}Iteration 3:  Maximum absolute difference ={res}    .01512
{txt}Iteration 4:  Maximum absolute difference ={res}   .008241
{txt}Iteration 5:  Maximum absolute difference ={res}   .005819
{txt}Iteration 6:  Maximum absolute difference ={res}   .006616
{txt}Iteration 7:  Maximum absolute difference ={res}   .002405
{txt}Iteration 8:  Maximum absolute difference ={res}  .0007313
{txt}Iteration 9:  Maximum absolute difference ={res}  .0001232
{txt}Iteration 10: Maximum absolute difference ={res} .00008679
{txt}Iteration 11: Maximum absolute difference ={res}  .0001124
{txt}Iteration 12: Maximum absolute difference ={res} .00002592
{txt}Iteration 13: Maximum absolute difference ={res} .00001074
{txt}Iteration 14: Maximum absolute difference ={res} 6.606e-06
{txt}Iteration 15: Maximum absolute difference ={res} 2.641e-06
{txt}Iteration 16: Maximum absolute difference ={res} 1.023e-06
{txt}Iteration 17: Maximum absolute difference ={res} 4.434e-07
{txt}Iteration 18: Maximum absolute difference ={res} 3.751e-08
{txt}Iteration 19: Maximum absolute difference ={res} 8.370e-09

{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 13:Number of obs}{col 66} = {res}{ralign 10:13,989,228}
{txt}{col 53}{lalign 13:Cluster comb.}{col 66} = {res}{ralign 10:3}
{txt}{col 1}Clusters per comb.:{col 53}{lalign 13:F({res:3}, {res:159})}{col 66} = {res}{ralign 10:17.22}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 6:160}{txt}{col 53}{lalign 13:Prob > F}{col 66} = {res}{ralign 10:0.0000}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 6:8,596}{txt}{col 53}{lalign 13:R-squared}{col 66} = {res}{ralign 10:0.5507}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 6:21,610}{txt}{col 53}{lalign 13:Adj R-squared}{col 66} = {res}{ralign 10:0.5489}
{txt}{col 53}{lalign 13:Root MSE}{col 66} = {res}{ralign 10:0.3346}

{txt}{ralign 78:(Std. err. adjusted for multiway clustering)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}reppartyvote{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}leader_next {c |}{col 14}{res}{space 2}  .049123{col 26}{space 2} .1118295{col 37}{space 1}    0.44{col 46}{space 3}0.661{col 54}{space 4}-.1717399{col 67}{space 3} .2699859
{txt}{space 2}leader_cvp {c |}{col 14}{res}{space 2} -.050435{col 26}{space 2} .1275191{col 37}{space 1}   -0.40{col 46}{space 3}0.693{col 54}{space 4}-.3022847{col 67}{space 3} .2014147
{txt}{space 1}leader_prev {c |}{col 14}{res}{space 2}  .568218{col 26}{space 2} .1123534{col 37}{space 1}    5.06{col 46}{space 3}0.000{col 54}{space 4} .3463205{col 67}{space 3} .7901155
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .3505839{col 26}{space 2} .0163693{col 37}{space 1}   21.42{col 46}{space 3}0.000{col 54}{space 4} .3182545{col 67}{space 3} .3829133
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table1_republicandirection.txt", append 2aster dec(3) sortvar(leader_next leader_cvp leader_prev)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table1_republicandirection.txt""':seeout}

{com}. areg reppartyvote leader_cvp leader_cvp_house, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}     .0374
{txt}Iteration 2:  Maximum absolute difference ={res}    .02544
{txt}Iteration 3:  Maximum absolute difference ={res}    .01871
{txt}Iteration 4:  Maximum absolute difference ={res}    .00764
{txt}Iteration 5:  Maximum absolute difference ={res}   .003482
{txt}Iteration 6:  Maximum absolute difference ={res}   .003424
{txt}Iteration 7:  Maximum absolute difference ={res}    .00296
{txt}Iteration 8:  Maximum absolute difference ={res}     .0017
{txt}Iteration 9:  Maximum absolute difference ={res}   .000648
{txt}Iteration 10: Maximum absolute difference ={res}   .000247
{txt}Iteration 11: Maximum absolute difference ={res}  .0001668
{txt}Iteration 12: Maximum absolute difference ={res}    .00003
{txt}Iteration 13: Maximum absolute difference ={res} .00004226
{txt}Iteration 14: Maximum absolute difference ={res} .00001391
{txt}Iteration 15: Maximum absolute difference ={res} 6.269e-06
{txt}Iteration 16: Maximum absolute difference ={res} 1.255e-06
{txt}Iteration 17: Maximum absolute difference ={res} 1.356e-07
{txt}Iteration 18: Maximum absolute difference ={res} 2.877e-08
{txt}Iteration 19: Maximum absolute difference ={res} 5.191e-09

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}    .05072
{txt}Iteration 2:  Maximum absolute difference ={res}     .0215
{txt}Iteration 3:  Maximum absolute difference ={res}    .01512
{txt}Iteration 4:  Maximum absolute difference ={res}   .007332
{txt}Iteration 5:  Maximum absolute difference ={res}   .005705
{txt}Iteration 6:  Maximum absolute difference ={res}   .005201
{txt}Iteration 7:  Maximum absolute difference ={res}   .002405
{txt}Iteration 8:  Maximum absolute difference ={res}  .0006931
{txt}Iteration 9:  Maximum absolute difference ={res}  .0001041
{txt}Iteration 10: Maximum absolute difference ={res} .00008679
{txt}Iteration 11: Maximum absolute difference ={res}  .0001124
{txt}Iteration 12: Maximum absolute difference ={res} .00002002
{txt}Iteration 13: Maximum absolute difference ={res} .00001074
{txt}Iteration 14: Maximum absolute difference ={res} 6.606e-06
{txt}Iteration 15: Maximum absolute difference ={res} 2.641e-06
{txt}Iteration 16: Maximum absolute difference ={res} 1.002e-06
{txt}Iteration 17: Maximum absolute difference ={res} 4.247e-07
{txt}Iteration 18: Maximum absolute difference ={res} 2.650e-08
{txt}Iteration 19: Maximum absolute difference ={res} 4.510e-09

{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 13:Number of obs}{col 66} = {res}{ralign 10:13,989,228}
{txt}{col 53}{lalign 13:Cluster comb.}{col 66} = {res}{ralign 10:3}
{txt}{col 1}Clusters per comb.:{col 53}{lalign 13:F({res:2}, {res:159})}{col 66} = {res}{ralign 10:14.55}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 6:160}{txt}{col 53}{lalign 13:Prob > F}{col 66} = {res}{ralign 10:0.0000}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 6:8,596}{txt}{col 53}{lalign 13:R-squared}{col 66} = {res}{ralign 10:0.5504}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 6:21,610}{txt}{col 53}{lalign 13:Adj R-squared}{col 66} = {res}{ralign 10:0.5485}
{txt}{col 53}{lalign 13:Root MSE}{col 66} = {res}{ralign 10:0.3348}

{txt}{ralign 82:(Std. err. adjusted for multiway clustering)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}    reppartyvote{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}leader_cvp {c |}{col 18}{res}{space 2} .1694055{col 30}{space 2} .0596306{col 41}{space 1}    2.84{col 50}{space 3}0.005{col 58}{space 4} .0516354{col 71}{space 3} .2871757
{txt}leader_cvp_house {c |}{col 18}{res}{space 2} .4190546{col 30}{space 2} .1414806{col 41}{space 1}    2.96{col 50}{space 3}0.004{col 58}{space 4} .1396309{col 71}{space 3} .6984783
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .3474214{col 30}{space 2}  .024252{col 41}{space 1}   14.33{col 50}{space 3}0.000{col 58}{space 4} .2995238{col 71}{space 3}  .395319
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table1_republicandirection.txt", append 2aster dec(3) sortvar(leader_next leader_cvp leader_prev)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table1_republicandirection.txt""':seeout}

{com}. areg reppartyvote leader_cvp leader_cvp_dem, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}     .0374
{txt}Iteration 2:  Maximum absolute difference ={res}    .02544
{txt}Iteration 3:  Maximum absolute difference ={res}    .01871
{txt}Iteration 4:  Maximum absolute difference ={res}    .00764
{txt}Iteration 5:  Maximum absolute difference ={res}   .003482
{txt}Iteration 6:  Maximum absolute difference ={res}   .003424
{txt}Iteration 7:  Maximum absolute difference ={res}    .00296
{txt}Iteration 8:  Maximum absolute difference ={res}     .0017
{txt}Iteration 9:  Maximum absolute difference ={res}   .000648
{txt}Iteration 10: Maximum absolute difference ={res}   .000247
{txt}Iteration 11: Maximum absolute difference ={res}  .0001668
{txt}Iteration 12: Maximum absolute difference ={res}    .00003
{txt}Iteration 13: Maximum absolute difference ={res} .00004226
{txt}Iteration 14: Maximum absolute difference ={res} .00001391
{txt}Iteration 15: Maximum absolute difference ={res} 6.269e-06
{txt}Iteration 16: Maximum absolute difference ={res} 1.255e-06
{txt}Iteration 17: Maximum absolute difference ={res} 1.356e-07
{txt}Iteration 18: Maximum absolute difference ={res} 2.877e-08
{txt}Iteration 19: Maximum absolute difference ={res} 5.191e-09

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}    .05072
{txt}Iteration 2:  Maximum absolute difference ={res}     .0215
{txt}Iteration 3:  Maximum absolute difference ={res}    .01512
{txt}Iteration 4:  Maximum absolute difference ={res}   .007332
{txt}Iteration 5:  Maximum absolute difference ={res}   .005705
{txt}Iteration 6:  Maximum absolute difference ={res}   .005201
{txt}Iteration 7:  Maximum absolute difference ={res}   .002405
{txt}Iteration 8:  Maximum absolute difference ={res}   .001053
{txt}Iteration 9:  Maximum absolute difference ={res}  .0001041
{txt}Iteration 10: Maximum absolute difference ={res} .00008679
{txt}Iteration 11: Maximum absolute difference ={res}  .0001124
{txt}Iteration 12: Maximum absolute difference ={res} .00002002
{txt}Iteration 13: Maximum absolute difference ={res} .00001074
{txt}Iteration 14: Maximum absolute difference ={res} 6.606e-06
{txt}Iteration 15: Maximum absolute difference ={res} 2.641e-06
{txt}Iteration 16: Maximum absolute difference ={res} 1.002e-06
{txt}Iteration 17: Maximum absolute difference ={res} 4.247e-07
{txt}Iteration 18: Maximum absolute difference ={res} 2.650e-08
{txt}Iteration 19: Maximum absolute difference ={res} 4.510e-09

{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 13:Number of obs}{col 66} = {res}{ralign 10:13,989,228}
{txt}{col 53}{lalign 13:Cluster comb.}{col 66} = {res}{ralign 10:3}
{txt}{col 1}Clusters per comb.:{col 53}{lalign 13:F({res:2}, {res:159})}{col 66} = {res}{ralign 10:16.17}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 6:160}{txt}{col 53}{lalign 13:Prob > F}{col 66} = {res}{ralign 10:0.0000}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 6:8,596}{txt}{col 53}{lalign 13:R-squared}{col 66} = {res}{ralign 10:0.5503}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 6:21,610}{txt}{col 53}{lalign 13:Adj R-squared}{col 66} = {res}{ralign 10:0.5485}
{txt}{col 53}{lalign 13:Root MSE}{col 66} = {res}{ralign 10:0.3348}

{txt}{ralign 80:(Std. err. adjusted for multiway clustering)}
{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}  reppartyvote{col 16}{c |} Coefficient{col 28}  std. err.{col 40}      t{col 48}   P>|t|{col 56}     [95% con{col 69}f. interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}leader_cvp {c |}{col 16}{res}{space 2} .4356236{col 28}{space 2} .0823092{col 39}{space 1}    5.29{col 48}{space 3}0.000{col 56}{space 4} .2730631{col 69}{space 3}  .598184
{txt}leader_cvp_dem {c |}{col 16}{res}{space 2} -.137468{col 28}{space 2} .1837147{col 39}{space 1}   -0.75{col 48}{space 3}0.455{col 56}{space 4}-.5003038{col 69}{space 3} .2253677
{txt}{space 9}_cons {c |}{col 16}{res}{space 2} .3689802{col 28}{space 2} .0214392{col 39}{space 1}   17.21{col 48}{space 3}0.000{col 56}{space 4} .3266379{col 69}{space 3} .4113225
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table1_republicandirection.txt", append 2aster dec(3) sortvar(leader_next leader_cvp leader_prev)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table1_republicandirection.txt""':seeout}

{com}. areg reppartyvote leader_cvp leader_cvp_majority, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}     .0374
{txt}Iteration 2:  Maximum absolute difference ={res}    .02544
{txt}Iteration 3:  Maximum absolute difference ={res}    .01871
{txt}Iteration 4:  Maximum absolute difference ={res}    .00764
{txt}Iteration 5:  Maximum absolute difference ={res}   .003482
{txt}Iteration 6:  Maximum absolute difference ={res}   .003424
{txt}Iteration 7:  Maximum absolute difference ={res}    .00296
{txt}Iteration 8:  Maximum absolute difference ={res}     .0017
{txt}Iteration 9:  Maximum absolute difference ={res}   .000648
{txt}Iteration 10: Maximum absolute difference ={res}   .000247
{txt}Iteration 11: Maximum absolute difference ={res}  .0001668
{txt}Iteration 12: Maximum absolute difference ={res}    .00003
{txt}Iteration 13: Maximum absolute difference ={res} .00004226
{txt}Iteration 14: Maximum absolute difference ={res} .00001391
{txt}Iteration 15: Maximum absolute difference ={res} 6.269e-06
{txt}Iteration 16: Maximum absolute difference ={res} 1.255e-06
{txt}Iteration 17: Maximum absolute difference ={res} 1.356e-07
{txt}Iteration 18: Maximum absolute difference ={res} 2.877e-08
{txt}Iteration 19: Maximum absolute difference ={res} 5.191e-09

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}     .1015
{txt}Iteration 2:  Maximum absolute difference ={res}    .05568
{txt}Iteration 3:  Maximum absolute difference ={res}    .05893
{txt}Iteration 4:  Maximum absolute difference ={res}    .02669
{txt}Iteration 5:  Maximum absolute difference ={res}    .05127
{txt}Iteration 6:  Maximum absolute difference ={res}    .02269
{txt}Iteration 7:  Maximum absolute difference ={res}   .007504
{txt}Iteration 8:  Maximum absolute difference ={res}   .004196
{txt}Iteration 9:  Maximum absolute difference ={res}   .001672
{txt}Iteration 10: Maximum absolute difference ={res}   .001032
{txt}Iteration 11: Maximum absolute difference ={res}  .0004369
{txt}Iteration 12: Maximum absolute difference ={res}  .0003134
{txt}Iteration 13: Maximum absolute difference ={res}  .0002368
{txt}Iteration 14: Maximum absolute difference ={res}  .0000242
{txt}Iteration 15: Maximum absolute difference ={res} 4.047e-06
{txt}Iteration 16: Maximum absolute difference ={res} 1.002e-06
{txt}Iteration 17: Maximum absolute difference ={res} 4.247e-07
{txt}Iteration 18: Maximum absolute difference ={res} 2.941e-08
{txt}Iteration 19: Maximum absolute difference ={res} 4.510e-09

{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 13:Number of obs}{col 66} = {res}{ralign 10:13,989,228}
{txt}{col 53}{lalign 13:Cluster comb.}{col 66} = {res}{ralign 10:3}
{txt}{col 1}Clusters per comb.:{col 53}{lalign 13:F({res:2}, {res:159})}{col 66} = {res}{ralign 10:13.61}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 6:160}{txt}{col 53}{lalign 13:Prob > F}{col 66} = {res}{ralign 10:0.0000}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 6:8,596}{txt}{col 53}{lalign 13:R-squared}{col 66} = {res}{ralign 10:0.5503}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 6:21,610}{txt}{col 53}{lalign 13:Adj R-squared}{col 66} = {res}{ralign 10:0.5484}
{txt}{col 53}{lalign 13:Root MSE}{col 66} = {res}{ralign 10:0.3348}

{txt}{ralign 85:(Std. err. adjusted for multiway clustering)}
{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}       reppartyvote{col 21}{c |} Coefficient{col 33}  std. err.{col 45}      t{col 53}   P>|t|{col 61}     [95% con{col 74}f. interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}leader_cvp {c |}{col 21}{res}{space 2} .3917831{col 33}{space 2} .0806495{col 44}{space 1}    4.86{col 53}{space 3}0.000{col 61}{space 4} .2325006{col 74}{space 3} .5510656
{txt}leader_cvp_majority {c |}{col 21}{res}{space 2}-.0140837{col 33}{space 2} .0333191{col 44}{space 1}   -0.42{col 53}{space 3}0.673{col 61}{space 4}-.0798888{col 74}{space 3} .0517215
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} .3849092{col 33}{space 2} .0145592{col 44}{space 1}   26.44{col 53}{space 3}0.000{col 61}{space 4} .3561548{col 74}{space 3} .4136637
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table1_republicandirection.txt", append 2aster dec(3) sortvar(leader_next leader_cvp leader_prev)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table1_republicandirection.txt""':seeout}

{com}. areg reppartyvote leader_cvp leader_cvp_moderate, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}     .0374
{txt}Iteration 2:  Maximum absolute difference ={res}    .02544
{txt}Iteration 3:  Maximum absolute difference ={res}    .01871
{txt}Iteration 4:  Maximum absolute difference ={res}    .00764
{txt}Iteration 5:  Maximum absolute difference ={res}   .003482
{txt}Iteration 6:  Maximum absolute difference ={res}   .003424
{txt}Iteration 7:  Maximum absolute difference ={res}    .00296
{txt}Iteration 8:  Maximum absolute difference ={res}     .0017
{txt}Iteration 9:  Maximum absolute difference ={res}   .000648
{txt}Iteration 10: Maximum absolute difference ={res}   .000247
{txt}Iteration 11: Maximum absolute difference ={res}  .0001668
{txt}Iteration 12: Maximum absolute difference ={res}    .00003
{txt}Iteration 13: Maximum absolute difference ={res} .00004226
{txt}Iteration 14: Maximum absolute difference ={res} .00001391
{txt}Iteration 15: Maximum absolute difference ={res} 6.269e-06
{txt}Iteration 16: Maximum absolute difference ={res} 1.255e-06
{txt}Iteration 17: Maximum absolute difference ={res} 1.356e-07
{txt}Iteration 18: Maximum absolute difference ={res} 2.877e-08
{txt}Iteration 19: Maximum absolute difference ={res} 5.191e-09

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}    .05072
{txt}Iteration 2:  Maximum absolute difference ={res}     .0215
{txt}Iteration 3:  Maximum absolute difference ={res}    .01512
{txt}Iteration 4:  Maximum absolute difference ={res}   .007332
{txt}Iteration 5:  Maximum absolute difference ={res}   .005705
{txt}Iteration 6:  Maximum absolute difference ={res}   .005201
{txt}Iteration 7:  Maximum absolute difference ={res}   .002405
{txt}Iteration 8:  Maximum absolute difference ={res}  .0006931
{txt}Iteration 9:  Maximum absolute difference ={res}  .0001041
{txt}Iteration 10: Maximum absolute difference ={res}  .0001422
{txt}Iteration 11: Maximum absolute difference ={res}  .0001124
{txt}Iteration 12: Maximum absolute difference ={res} .00002002
{txt}Iteration 13: Maximum absolute difference ={res} .00001074
{txt}Iteration 14: Maximum absolute difference ={res} 6.606e-06
{txt}Iteration 15: Maximum absolute difference ={res} 2.641e-06
{txt}Iteration 16: Maximum absolute difference ={res} 1.002e-06
{txt}Iteration 17: Maximum absolute difference ={res} 4.247e-07
{txt}Iteration 18: Maximum absolute difference ={res} 2.650e-08
{txt}Iteration 19: Maximum absolute difference ={res} 4.510e-09

{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 13:Number of obs}{col 66} = {res}{ralign 10:13,989,228}
{txt}{col 53}{lalign 13:Cluster comb.}{col 66} = {res}{ralign 10:3}
{txt}{col 1}Clusters per comb.:{col 53}{lalign 13:F({res:2}, {res:159})}{col 66} = {res}{ralign 10:14.94}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 6:160}{txt}{col 53}{lalign 13:Prob > F}{col 66} = {res}{ralign 10:0.0000}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 6:8,596}{txt}{col 53}{lalign 13:R-squared}{col 66} = {res}{ralign 10:0.5503}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 6:21,610}{txt}{col 53}{lalign 13:Adj R-squared}{col 66} = {res}{ralign 10:0.5485}
{txt}{col 53}{lalign 13:Root MSE}{col 66} = {res}{ralign 10:0.3348}

{txt}{ralign 85:(Std. err. adjusted for multiway clustering)}
{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}       reppartyvote{col 21}{c |} Coefficient{col 33}  std. err.{col 45}      t{col 53}   P>|t|{col 61}     [95% con{col 74}f. interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}leader_cvp {c |}{col 21}{res}{space 2} .3075568{col 33}{space 2} .0824712{col 44}{space 1}    3.73{col 53}{space 3}0.000{col 61}{space 4} .1446765{col 74}{space 3}  .470437
{txt}leader_cvp_moderate {c |}{col 21}{res}{space 2} .1523696{col 33}{space 2} .0708493{col 44}{space 1}    2.15{col 53}{space 3}0.033{col 61}{space 4} .0124425{col 74}{space 3} .2922967
{txt}{space 14}_cons {c |}{col 21}{res}{space 2}  .385655{col 33}{space 2} .0145815{col 44}{space 1}   26.45{col 53}{space 3}0.000{col 61}{space 4} .3568566{col 74}{space 3} .4144534
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table1_republicandirection.txt", append 2aster dec(3) sortvar(leader_next leader_cvp leader_prev)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table1_republicandirection.txt""':seeout}

{com}. 
. areg withrepublicans leader_cvp, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}    .04526
{txt}Iteration 2:  Maximum absolute difference ={res}    .04361
{txt}Iteration 3:  Maximum absolute difference ={res}    .03403
{txt}Iteration 4:  Maximum absolute difference ={res}   .006116
{txt}Iteration 5:  Maximum absolute difference ={res}    .01891
{txt}Iteration 6:  Maximum absolute difference ={res}    .01023
{txt}Iteration 7:  Maximum absolute difference ={res}   .003496
{txt}Iteration 8:  Maximum absolute difference ={res}   .002038
{txt}Iteration 9:  Maximum absolute difference ={res}   .001245
{txt}Iteration 10: Maximum absolute difference ={res}  .0002316
{txt}Iteration 11: Maximum absolute difference ={res} .00007754
{txt}Iteration 12: Maximum absolute difference ={res} .00003284
{txt}Iteration 13: Maximum absolute difference ={res} .00005757
{txt}Iteration 14: Maximum absolute difference ={res} .00001421
{txt}Iteration 15: Maximum absolute difference ={res} 2.964e-06
{txt}Iteration 16: Maximum absolute difference ={res} 1.058e-06
{txt}Iteration 17: Maximum absolute difference ={res} 3.687e-07
{txt}Iteration 18: Maximum absolute difference ={res} 8.475e-08
{txt}Iteration 19: Maximum absolute difference ={res} 6.138e-09

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}    .05072
{txt}Iteration 2:  Maximum absolute difference ={res}     .0215
{txt}Iteration 3:  Maximum absolute difference ={res}    .01512
{txt}Iteration 4:  Maximum absolute difference ={res}   .007332
{txt}Iteration 5:  Maximum absolute difference ={res}   .005705
{txt}Iteration 6:  Maximum absolute difference ={res}   .005201
{txt}Iteration 7:  Maximum absolute difference ={res}   .002405
{txt}Iteration 8:  Maximum absolute difference ={res}  .0006931
{txt}Iteration 9:  Maximum absolute difference ={res}  .0001041
{txt}Iteration 10: Maximum absolute difference ={res} .00008679
{txt}Iteration 11: Maximum absolute difference ={res}  .0001124
{txt}Iteration 12: Maximum absolute difference ={res} .00002002
{txt}Iteration 13: Maximum absolute difference ={res} .00001074
{txt}Iteration 14: Maximum absolute difference ={res} 6.606e-06
{txt}Iteration 15: Maximum absolute difference ={res} 2.641e-06
{txt}Iteration 16: Maximum absolute difference ={res} 1.002e-06
{txt}Iteration 17: Maximum absolute difference ={res} 4.247e-07
{txt}Iteration 18: Maximum absolute difference ={res} 2.650e-08
{txt}Iteration 19: Maximum absolute difference ={res} 4.510e-09

{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 13:Number of obs}{col 66} = {res}{ralign 10:13,989,228}
{txt}{col 53}{lalign 13:Cluster comb.}{col 66} = {res}{ralign 10:3}
{txt}{col 1}Clusters per comb.:{col 53}{lalign 13:F({res:1}, {res:159})}{col 66} = {res}{ralign 10:36.43}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 6:160}{txt}{col 53}{lalign 13:Prob > F}{col 66} = {res}{ralign 10:0.0000}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 6:8,596}{txt}{col 53}{lalign 13:R-squared}{col 66} = {res}{ralign 10:0.4433}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 6:21,610}{txt}{col 53}{lalign 13:Adj R-squared}{col 66} = {res}{ralign 10:0.4410}
{txt}{col 53}{lalign 13:Root MSE}{col 66} = {res}{ralign 10:0.3591}

{txt}{ralign 78:(Std. err. adjusted for multiway clustering)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}withrepubl~s{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}leader_cvp {c |}{col 14}{res}{space 2} .4924553{col 26}{space 2} .0815871{col 37}{space 1}    6.04{col 46}{space 3}0.000{col 54}{space 4} .3313211{col 67}{space 3} .6535895
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .5454517{col 26}{space 2} .0157548{col 37}{space 1}   34.62{col 46}{space 3}0.000{col 54}{space 4} .5143361{col 67}{space 3} .5765673
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table1_withrepublicans.txt", replace 2aster dec(3) sortvar(leader_next leader_cvp leader_prev)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table1_withrepublicans.txt""':seeout}

{com}. areg withrepublicans leader_next leader_cvp, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}    .04526
{txt}Iteration 2:  Maximum absolute difference ={res}    .04361
{txt}Iteration 3:  Maximum absolute difference ={res}    .03403
{txt}Iteration 4:  Maximum absolute difference ={res}   .006116
{txt}Iteration 5:  Maximum absolute difference ={res}    .01891
{txt}Iteration 6:  Maximum absolute difference ={res}    .01023
{txt}Iteration 7:  Maximum absolute difference ={res}   .003496
{txt}Iteration 8:  Maximum absolute difference ={res}   .002038
{txt}Iteration 9:  Maximum absolute difference ={res}   .001245
{txt}Iteration 10: Maximum absolute difference ={res}  .0002316
{txt}Iteration 11: Maximum absolute difference ={res} .00007754
{txt}Iteration 12: Maximum absolute difference ={res} .00003284
{txt}Iteration 13: Maximum absolute difference ={res} .00005757
{txt}Iteration 14: Maximum absolute difference ={res} .00001421
{txt}Iteration 15: Maximum absolute difference ={res} 2.964e-06
{txt}Iteration 16: Maximum absolute difference ={res} 1.058e-06
{txt}Iteration 17: Maximum absolute difference ={res} 3.687e-07
{txt}Iteration 18: Maximum absolute difference ={res} 8.475e-08
{txt}Iteration 19: Maximum absolute difference ={res} 6.138e-09

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}    .05072
{txt}Iteration 2:  Maximum absolute difference ={res}     .0215
{txt}Iteration 3:  Maximum absolute difference ={res}    .01512
{txt}Iteration 4:  Maximum absolute difference ={res}   .007332
{txt}Iteration 5:  Maximum absolute difference ={res}   .005705
{txt}Iteration 6:  Maximum absolute difference ={res}   .005201
{txt}Iteration 7:  Maximum absolute difference ={res}   .002405
{txt}Iteration 8:  Maximum absolute difference ={res}  .0007313
{txt}Iteration 9:  Maximum absolute difference ={res}  .0001041
{txt}Iteration 10: Maximum absolute difference ={res} .00008679
{txt}Iteration 11: Maximum absolute difference ={res}  .0001124
{txt}Iteration 12: Maximum absolute difference ={res} .00002002
{txt}Iteration 13: Maximum absolute difference ={res} .00001074
{txt}Iteration 14: Maximum absolute difference ={res} 6.606e-06
{txt}Iteration 15: Maximum absolute difference ={res} 2.641e-06
{txt}Iteration 16: Maximum absolute difference ={res} 1.023e-06
{txt}Iteration 17: Maximum absolute difference ={res} 4.247e-07
{txt}Iteration 18: Maximum absolute difference ={res} 3.087e-08
{txt}Iteration 19: Maximum absolute difference ={res} 8.370e-09

{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 13:Number of obs}{col 66} = {res}{ralign 10:13,989,228}
{txt}{col 53}{lalign 13:Cluster comb.}{col 66} = {res}{ralign 10:3}
{txt}{col 1}Clusters per comb.:{col 53}{lalign 13:F({res:2}, {res:159})}{col 66} = {res}{ralign 10:18.90}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 6:160}{txt}{col 53}{lalign 13:Prob > F}{col 66} = {res}{ralign 10:0.0000}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 6:8,596}{txt}{col 53}{lalign 13:R-squared}{col 66} = {res}{ralign 10:0.4433}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 6:21,610}{txt}{col 53}{lalign 13:Adj R-squared}{col 66} = {res}{ralign 10:0.4410}
{txt}{col 53}{lalign 13:Root MSE}{col 66} = {res}{ralign 10:0.3591}

{txt}{ralign 78:(Std. err. adjusted for multiway clustering)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}withrepubl~s{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}leader_next {c |}{col 14}{res}{space 2} .1218622{col 26}{space 2} .1058887{col 37}{space 1}    1.15{col 46}{space 3}0.252{col 54}{space 4}-.0872674{col 67}{space 3} .3309919
{txt}{space 2}leader_cvp {c |}{col 14}{res}{space 2} .4133881{col 26}{space 2} .1018211{col 37}{space 1}    4.06{col 46}{space 3}0.000{col 54}{space 4} .2122918{col 67}{space 3} .6144844
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .5372464{col 26}{space 2} .0176306{col 37}{space 1}   30.47{col 46}{space 3}0.000{col 54}{space 4}  .502426{col 67}{space 3} .5720667
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table1_withrepublicans.txt", append 2aster dec(3) sortvar(leader_next leader_cvp leader_prev)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table1_withrepublicans.txt""':seeout}

{com}. areg withrepublicans leader_next leader_cvp leader_prev, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}    .04526
{txt}Iteration 2:  Maximum absolute difference ={res}    .04361
{txt}Iteration 3:  Maximum absolute difference ={res}    .03403
{txt}Iteration 4:  Maximum absolute difference ={res}   .006116
{txt}Iteration 5:  Maximum absolute difference ={res}    .01891
{txt}Iteration 6:  Maximum absolute difference ={res}    .01023
{txt}Iteration 7:  Maximum absolute difference ={res}   .003496
{txt}Iteration 8:  Maximum absolute difference ={res}   .002038
{txt}Iteration 9:  Maximum absolute difference ={res}   .001245
{txt}Iteration 10: Maximum absolute difference ={res}  .0002316
{txt}Iteration 11: Maximum absolute difference ={res} .00007754
{txt}Iteration 12: Maximum absolute difference ={res} .00003284
{txt}Iteration 13: Maximum absolute difference ={res} .00005757
{txt}Iteration 14: Maximum absolute difference ={res} .00001421
{txt}Iteration 15: Maximum absolute difference ={res} 2.964e-06
{txt}Iteration 16: Maximum absolute difference ={res} 1.058e-06
{txt}Iteration 17: Maximum absolute difference ={res} 3.687e-07
{txt}Iteration 18: Maximum absolute difference ={res} 8.475e-08
{txt}Iteration 19: Maximum absolute difference ={res} 6.138e-09

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}    .05072
{txt}Iteration 2:  Maximum absolute difference ={res}     .0215
{txt}Iteration 3:  Maximum absolute difference ={res}    .01512
{txt}Iteration 4:  Maximum absolute difference ={res}   .008241
{txt}Iteration 5:  Maximum absolute difference ={res}   .005819
{txt}Iteration 6:  Maximum absolute difference ={res}   .006616
{txt}Iteration 7:  Maximum absolute difference ={res}   .002405
{txt}Iteration 8:  Maximum absolute difference ={res}  .0007313
{txt}Iteration 9:  Maximum absolute difference ={res}  .0001232
{txt}Iteration 10: Maximum absolute difference ={res} .00008679
{txt}Iteration 11: Maximum absolute difference ={res}  .0001124
{txt}Iteration 12: Maximum absolute difference ={res} .00002592
{txt}Iteration 13: Maximum absolute difference ={res} .00001074
{txt}Iteration 14: Maximum absolute difference ={res} 6.606e-06
{txt}Iteration 15: Maximum absolute difference ={res} 2.641e-06
{txt}Iteration 16: Maximum absolute difference ={res} 1.023e-06
{txt}Iteration 17: Maximum absolute difference ={res} 4.434e-07
{txt}Iteration 18: Maximum absolute difference ={res} 3.751e-08
{txt}Iteration 19: Maximum absolute difference ={res} 8.370e-09

{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 13:Number of obs}{col 66} = {res}{ralign 10:13,989,228}
{txt}{col 53}{lalign 13:Cluster comb.}{col 66} = {res}{ralign 10:3}
{txt}{col 1}Clusters per comb.:{col 53}{lalign 13:F({res:3}, {res:159})}{col 66} = {res}{ralign 10:19.75}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 6:160}{txt}{col 53}{lalign 13:Prob > F}{col 66} = {res}{ralign 10:0.0000}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 6:8,596}{txt}{col 53}{lalign 13:R-squared}{col 66} = {res}{ralign 10:0.4438}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 6:21,610}{txt}{col 53}{lalign 13:Adj R-squared}{col 66} = {res}{ralign 10:0.4416}
{txt}{col 53}{lalign 13:Root MSE}{col 66} = {res}{ralign 10:0.3590}

{txt}{ralign 78:(Std. err. adjusted for multiway clustering)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}withrepubl~s{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}leader_next {c |}{col 14}{res}{space 2} .1323402{col 26}{space 2} .1107942{col 37}{space 1}    1.19{col 46}{space 3}0.234{col 54}{space 4}-.0864781{col 67}{space 3} .3511584
{txt}{space 2}leader_cvp {c |}{col 14}{res}{space 2}-.0335976{col 26}{space 2}  .126445{col 37}{space 1}   -0.27{col 46}{space 3}0.791{col 54}{space 4}-.2833259{col 67}{space 3} .2161308
{txt}{space 1}leader_prev {c |}{col 14}{res}{space 2} .6197196{col 26}{space 2} .1190688{col 37}{space 1}    5.20{col 46}{space 3}0.000{col 54}{space 4} .3845591{col 67}{space 3} .8548801
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .5025831{col 26}{space 2} .0191065{col 37}{space 1}   26.30{col 46}{space 3}0.000{col 54}{space 4} .4648479{col 67}{space 3} .5403183
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table1_withrepublicans.txt", append 2aster dec(3) sortvar(leader_next leader_cvp leader_prev)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table1_withrepublicans.txt""':seeout}

{com}. areg withrepublicans leader_cvp leader_cvp_house, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}    .04526
{txt}Iteration 2:  Maximum absolute difference ={res}    .04361
{txt}Iteration 3:  Maximum absolute difference ={res}    .03403
{txt}Iteration 4:  Maximum absolute difference ={res}   .006116
{txt}Iteration 5:  Maximum absolute difference ={res}    .01891
{txt}Iteration 6:  Maximum absolute difference ={res}    .01023
{txt}Iteration 7:  Maximum absolute difference ={res}   .003496
{txt}Iteration 8:  Maximum absolute difference ={res}   .002038
{txt}Iteration 9:  Maximum absolute difference ={res}   .001245
{txt}Iteration 10: Maximum absolute difference ={res}  .0002316
{txt}Iteration 11: Maximum absolute difference ={res} .00007754
{txt}Iteration 12: Maximum absolute difference ={res} .00003284
{txt}Iteration 13: Maximum absolute difference ={res} .00005757
{txt}Iteration 14: Maximum absolute difference ={res} .00001421
{txt}Iteration 15: Maximum absolute difference ={res} 2.964e-06
{txt}Iteration 16: Maximum absolute difference ={res} 1.058e-06
{txt}Iteration 17: Maximum absolute difference ={res} 3.687e-07
{txt}Iteration 18: Maximum absolute difference ={res} 8.475e-08
{txt}Iteration 19: Maximum absolute difference ={res} 6.138e-09

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}    .05072
{txt}Iteration 2:  Maximum absolute difference ={res}     .0215
{txt}Iteration 3:  Maximum absolute difference ={res}    .01512
{txt}Iteration 4:  Maximum absolute difference ={res}   .007332
{txt}Iteration 5:  Maximum absolute difference ={res}   .005705
{txt}Iteration 6:  Maximum absolute difference ={res}   .005201
{txt}Iteration 7:  Maximum absolute difference ={res}   .002405
{txt}Iteration 8:  Maximum absolute difference ={res}  .0006931
{txt}Iteration 9:  Maximum absolute difference ={res}  .0001041
{txt}Iteration 10: Maximum absolute difference ={res} .00008679
{txt}Iteration 11: Maximum absolute difference ={res}  .0001124
{txt}Iteration 12: Maximum absolute difference ={res} .00002002
{txt}Iteration 13: Maximum absolute difference ={res} .00001074
{txt}Iteration 14: Maximum absolute difference ={res} 6.606e-06
{txt}Iteration 15: Maximum absolute difference ={res} 2.641e-06
{txt}Iteration 16: Maximum absolute difference ={res} 1.002e-06
{txt}Iteration 17: Maximum absolute difference ={res} 4.247e-07
{txt}Iteration 18: Maximum absolute difference ={res} 2.650e-08
{txt}Iteration 19: Maximum absolute difference ={res} 4.510e-09

{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 13:Number of obs}{col 66} = {res}{ralign 10:13,989,228}
{txt}{col 53}{lalign 13:Cluster comb.}{col 66} = {res}{ralign 10:3}
{txt}{col 1}Clusters per comb.:{col 53}{lalign 13:F({res:2}, {res:159})}{col 66} = {res}{ralign 10:20.85}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 6:160}{txt}{col 53}{lalign 13:Prob > F}{col 66} = {res}{ralign 10:0.0000}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 6:8,596}{txt}{col 53}{lalign 13:R-squared}{col 66} = {res}{ralign 10:0.4434}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 6:21,610}{txt}{col 53}{lalign 13:Adj R-squared}{col 66} = {res}{ralign 10:0.4412}
{txt}{col 53}{lalign 13:Root MSE}{col 66} = {res}{ralign 10:0.3591}

{txt}{ralign 82:(Std. err. adjusted for multiway clustering)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1} withrepublicans{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}leader_cvp {c |}{col 18}{res}{space 2} .2547992{col 30}{space 2} .0684093{col 41}{space 1}    3.72{col 50}{space 3}0.000{col 58}{space 4} .1196911{col 71}{space 3} .3899073
{txt}leader_cvp_house {c |}{col 18}{res}{space 2} .4618444{col 30}{space 2} .1521209{col 41}{space 1}    3.04{col 50}{space 3}0.003{col 58}{space 4} .1614062{col 71}{space 3} .7622826
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .5040059{col 30}{space 2} .0256603{col 41}{space 1}   19.64{col 50}{space 3}0.000{col 58}{space 4}  .453327{col 71}{space 3} .5546848
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table1_withrepublicans.txt", append 2aster dec(3) sortvar(leader_next leader_cvp leader_prev)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table1_withrepublicans.txt""':seeout}

{com}. areg withrepublicans leader_cvp leader_cvp_dem, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}    .04526
{txt}Iteration 2:  Maximum absolute difference ={res}    .04361
{txt}Iteration 3:  Maximum absolute difference ={res}    .03403
{txt}Iteration 4:  Maximum absolute difference ={res}   .006116
{txt}Iteration 5:  Maximum absolute difference ={res}    .01891
{txt}Iteration 6:  Maximum absolute difference ={res}    .01023
{txt}Iteration 7:  Maximum absolute difference ={res}   .003496
{txt}Iteration 8:  Maximum absolute difference ={res}   .002038
{txt}Iteration 9:  Maximum absolute difference ={res}   .001245
{txt}Iteration 10: Maximum absolute difference ={res}  .0002316
{txt}Iteration 11: Maximum absolute difference ={res} .00007754
{txt}Iteration 12: Maximum absolute difference ={res} .00003284
{txt}Iteration 13: Maximum absolute difference ={res} .00005757
{txt}Iteration 14: Maximum absolute difference ={res} .00001421
{txt}Iteration 15: Maximum absolute difference ={res} 2.964e-06
{txt}Iteration 16: Maximum absolute difference ={res} 1.058e-06
{txt}Iteration 17: Maximum absolute difference ={res} 3.687e-07
{txt}Iteration 18: Maximum absolute difference ={res} 8.475e-08
{txt}Iteration 19: Maximum absolute difference ={res} 6.138e-09

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}    .05072
{txt}Iteration 2:  Maximum absolute difference ={res}     .0215
{txt}Iteration 3:  Maximum absolute difference ={res}    .01512
{txt}Iteration 4:  Maximum absolute difference ={res}   .007332
{txt}Iteration 5:  Maximum absolute difference ={res}   .005705
{txt}Iteration 6:  Maximum absolute difference ={res}   .005201
{txt}Iteration 7:  Maximum absolute difference ={res}   .002405
{txt}Iteration 8:  Maximum absolute difference ={res}   .001053
{txt}Iteration 9:  Maximum absolute difference ={res}  .0001041
{txt}Iteration 10: Maximum absolute difference ={res} .00008679
{txt}Iteration 11: Maximum absolute difference ={res}  .0001124
{txt}Iteration 12: Maximum absolute difference ={res} .00002002
{txt}Iteration 13: Maximum absolute difference ={res} .00001074
{txt}Iteration 14: Maximum absolute difference ={res} 6.606e-06
{txt}Iteration 15: Maximum absolute difference ={res} 2.641e-06
{txt}Iteration 16: Maximum absolute difference ={res} 1.002e-06
{txt}Iteration 17: Maximum absolute difference ={res} 4.247e-07
{txt}Iteration 18: Maximum absolute difference ={res} 2.650e-08
{txt}Iteration 19: Maximum absolute difference ={res} 4.510e-09

{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 13:Number of obs}{col 66} = {res}{ralign 10:13,989,228}
{txt}{col 53}{lalign 13:Cluster comb.}{col 66} = {res}{ralign 10:3}
{txt}{col 1}Clusters per comb.:{col 53}{lalign 13:F({res:2}, {res:159})}{col 66} = {res}{ralign 10:21.23}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 6:160}{txt}{col 53}{lalign 13:Prob > F}{col 66} = {res}{ralign 10:0.0000}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 6:8,596}{txt}{col 53}{lalign 13:R-squared}{col 66} = {res}{ralign 10:0.4433}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 6:21,610}{txt}{col 53}{lalign 13:Adj R-squared}{col 66} = {res}{ralign 10:0.4410}
{txt}{col 53}{lalign 13:Root MSE}{col 66} = {res}{ralign 10:0.3591}

{txt}{ralign 80:(Std. err. adjusted for multiway clustering)}
{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}withrepublic~s{col 16}{c |} Coefficient{col 28}  std. err.{col 40}      t{col 48}   P>|t|{col 56}     [95% con{col 69}f. interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}leader_cvp {c |}{col 16}{res}{space 2} .5524217{col 28}{space 2} .0899698{col 39}{space 1}    6.14{col 48}{space 3}0.000{col 56}{space 4} .3747317{col 69}{space 3} .7301118
{txt}leader_cvp_dem {c |}{col 16}{res}{space 2}-.1629766{col 28}{space 2} .1809009{col 39}{space 1}   -0.90{col 48}{space 3}0.369{col 56}{space 4}-.5202551{col 69}{space 3} .1943019
{txt}{space 9}_cons {c |}{col 16}{res}{space 2}  .526427{col 28}{space 2} .0225927{col 39}{space 1}   23.30{col 48}{space 3}0.000{col 56}{space 4} .4818065{col 69}{space 3} .5710474
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table1_withrepublicans.txt", append 2aster dec(3) sortvar(leader_next leader_cvp leader_prev)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table1_withrepublicans.txt""':seeout}

{com}. areg withrepublicans leader_cvp leader_cvp_majority, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}    .04526
{txt}Iteration 2:  Maximum absolute difference ={res}    .04361
{txt}Iteration 3:  Maximum absolute difference ={res}    .03403
{txt}Iteration 4:  Maximum absolute difference ={res}   .006116
{txt}Iteration 5:  Maximum absolute difference ={res}    .01891
{txt}Iteration 6:  Maximum absolute difference ={res}    .01023
{txt}Iteration 7:  Maximum absolute difference ={res}   .003496
{txt}Iteration 8:  Maximum absolute difference ={res}   .002038
{txt}Iteration 9:  Maximum absolute difference ={res}   .001245
{txt}Iteration 10: Maximum absolute difference ={res}  .0002316
{txt}Iteration 11: Maximum absolute difference ={res} .00007754
{txt}Iteration 12: Maximum absolute difference ={res} .00003284
{txt}Iteration 13: Maximum absolute difference ={res} .00005757
{txt}Iteration 14: Maximum absolute difference ={res} .00001421
{txt}Iteration 15: Maximum absolute difference ={res} 2.964e-06
{txt}Iteration 16: Maximum absolute difference ={res} 1.058e-06
{txt}Iteration 17: Maximum absolute difference ={res} 3.687e-07
{txt}Iteration 18: Maximum absolute difference ={res} 8.475e-08
{txt}Iteration 19: Maximum absolute difference ={res} 6.138e-09

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}     .1015
{txt}Iteration 2:  Maximum absolute difference ={res}    .05568
{txt}Iteration 3:  Maximum absolute difference ={res}    .05893
{txt}Iteration 4:  Maximum absolute difference ={res}    .02669
{txt}Iteration 5:  Maximum absolute difference ={res}    .05127
{txt}Iteration 6:  Maximum absolute difference ={res}    .02269
{txt}Iteration 7:  Maximum absolute difference ={res}   .007504
{txt}Iteration 8:  Maximum absolute difference ={res}   .004196
{txt}Iteration 9:  Maximum absolute difference ={res}   .001672
{txt}Iteration 10: Maximum absolute difference ={res}   .001032
{txt}Iteration 11: Maximum absolute difference ={res}  .0004369
{txt}Iteration 12: Maximum absolute difference ={res}  .0003134
{txt}Iteration 13: Maximum absolute difference ={res}  .0002368
{txt}Iteration 14: Maximum absolute difference ={res}  .0000242
{txt}Iteration 15: Maximum absolute difference ={res} 4.047e-06
{txt}Iteration 16: Maximum absolute difference ={res} 1.002e-06
{txt}Iteration 17: Maximum absolute difference ={res} 4.247e-07
{txt}Iteration 18: Maximum absolute difference ={res} 2.941e-08
{txt}Iteration 19: Maximum absolute difference ={res} 4.510e-09

{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 13:Number of obs}{col 66} = {res}{ralign 10:13,989,228}
{txt}{col 53}{lalign 13:Cluster comb.}{col 66} = {res}{ralign 10:3}
{txt}{col 1}Clusters per comb.:{col 53}{lalign 13:F({res:2}, {res:159})}{col 66} = {res}{ralign 10:22.29}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 6:160}{txt}{col 53}{lalign 13:Prob > F}{col 66} = {res}{ralign 10:0.0000}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 6:8,596}{txt}{col 53}{lalign 13:R-squared}{col 66} = {res}{ralign 10:0.4434}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 6:21,610}{txt}{col 53}{lalign 13:Adj R-squared}{col 66} = {res}{ralign 10:0.4412}
{txt}{col 53}{lalign 13:Root MSE}{col 66} = {res}{ralign 10:0.3591}

{txt}{ralign 85:(Std. err. adjusted for multiway clustering)}
{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}    withrepublicans{col 21}{c |} Coefficient{col 33}  std. err.{col 45}      t{col 53}   P>|t|{col 61}     [95% con{col 74}f. interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}leader_cvp {c |}{col 21}{res}{space 2} .4584768{col 33}{space 2} .0880219{col 44}{space 1}    5.21{col 53}{space 3}0.000{col 61}{space 4} .2846339{col 74}{space 3} .6323197
{txt}leader_cvp_majority {c |}{col 21}{res}{space 2}  .070998{col 33}{space 2}  .036704{col 44}{space 1}    1.93{col 53}{space 3}0.055{col 61}{space 4}-.0014923{col 74}{space 3} .1434884
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} .5460467{col 33}{space 2} .0161448{col 44}{space 1}   33.82{col 53}{space 3}0.000{col 61}{space 4} .5141607{col 74}{space 3} .5779326
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table1_withrepublicans.txt", append 2aster dec(3) sortvar(leader_next leader_cvp leader_prev)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table1_withrepublicans.txt""':seeout}

{com}. areg withrepublicans leader_cvp leader_cvp_moderate, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}    .04526
{txt}Iteration 2:  Maximum absolute difference ={res}    .04361
{txt}Iteration 3:  Maximum absolute difference ={res}    .03403
{txt}Iteration 4:  Maximum absolute difference ={res}   .006116
{txt}Iteration 5:  Maximum absolute difference ={res}    .01891
{txt}Iteration 6:  Maximum absolute difference ={res}    .01023
{txt}Iteration 7:  Maximum absolute difference ={res}   .003496
{txt}Iteration 8:  Maximum absolute difference ={res}   .002038
{txt}Iteration 9:  Maximum absolute difference ={res}   .001245
{txt}Iteration 10: Maximum absolute difference ={res}  .0002316
{txt}Iteration 11: Maximum absolute difference ={res} .00007754
{txt}Iteration 12: Maximum absolute difference ={res} .00003284
{txt}Iteration 13: Maximum absolute difference ={res} .00005757
{txt}Iteration 14: Maximum absolute difference ={res} .00001421
{txt}Iteration 15: Maximum absolute difference ={res} 2.964e-06
{txt}Iteration 16: Maximum absolute difference ={res} 1.058e-06
{txt}Iteration 17: Maximum absolute difference ={res} 3.687e-07
{txt}Iteration 18: Maximum absolute difference ={res} 8.475e-08
{txt}Iteration 19: Maximum absolute difference ={res} 6.138e-09

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}    .05072
{txt}Iteration 2:  Maximum absolute difference ={res}     .0215
{txt}Iteration 3:  Maximum absolute difference ={res}    .01512
{txt}Iteration 4:  Maximum absolute difference ={res}   .007332
{txt}Iteration 5:  Maximum absolute difference ={res}   .005705
{txt}Iteration 6:  Maximum absolute difference ={res}   .005201
{txt}Iteration 7:  Maximum absolute difference ={res}   .002405
{txt}Iteration 8:  Maximum absolute difference ={res}  .0006931
{txt}Iteration 9:  Maximum absolute difference ={res}  .0001041
{txt}Iteration 10: Maximum absolute difference ={res}  .0001422
{txt}Iteration 11: Maximum absolute difference ={res}  .0001124
{txt}Iteration 12: Maximum absolute difference ={res} .00002002
{txt}Iteration 13: Maximum absolute difference ={res} .00001074
{txt}Iteration 14: Maximum absolute difference ={res} 6.606e-06
{txt}Iteration 15: Maximum absolute difference ={res} 2.641e-06
{txt}Iteration 16: Maximum absolute difference ={res} 1.002e-06
{txt}Iteration 17: Maximum absolute difference ={res} 4.247e-07
{txt}Iteration 18: Maximum absolute difference ={res} 2.650e-08
{txt}Iteration 19: Maximum absolute difference ={res} 4.510e-09

{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 13:Number of obs}{col 66} = {res}{ralign 10:13,989,228}
{txt}{col 53}{lalign 13:Cluster comb.}{col 66} = {res}{ralign 10:3}
{txt}{col 1}Clusters per comb.:{col 53}{lalign 13:F({res:2}, {res:159})}{col 66} = {res}{ralign 10:19.07}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 6:160}{txt}{col 53}{lalign 13:Prob > F}{col 66} = {res}{ralign 10:0.0000}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 6:8,596}{txt}{col 53}{lalign 13:R-squared}{col 66} = {res}{ralign 10:0.4433}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 6:21,610}{txt}{col 53}{lalign 13:Adj R-squared}{col 66} = {res}{ralign 10:0.4410}
{txt}{col 53}{lalign 13:Root MSE}{col 66} = {res}{ralign 10:0.3591}

{txt}{ralign 85:(Std. err. adjusted for multiway clustering)}
{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}    withrepublicans{col 21}{c |} Coefficient{col 33}  std. err.{col 45}      t{col 53}   P>|t|{col 61}     [95% con{col 74}f. interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}leader_cvp {c |}{col 21}{res}{space 2} .4784949{col 33}{space 2}  .092314{col 44}{space 1}    5.18{col 53}{space 3}0.000{col 61}{space 4} .2961751{col 74}{space 3} .6608147
{txt}leader_cvp_moderate {c |}{col 21}{res}{space 2} .0274519{col 33}{space 2} .0646961{col 44}{space 1}    0.42{col 53}{space 3}0.672{col 61}{space 4}-.1003227{col 74}{space 3} .1552265
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} .5455648{col 33}{space 2} .0157971{col 44}{space 1}   34.54{col 53}{space 3}0.000{col 61}{space 4} .5143657{col 74}{space 3} .5767639
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table1_withrepublicans.txt", append 2aster dec(3) sortvar(leader_next leader_cvp leader_prev)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table1_withrepublicans.txt""':seeout}

{com}. 
. areg againstdemocrats leader_cvp, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}    .01653
{txt}Iteration 2:  Maximum absolute difference ={res}    .01068
{txt}Iteration 3:  Maximum absolute difference ={res}   .008038
{txt}Iteration 4:  Maximum absolute difference ={res}   .005906
{txt}Iteration 5:  Maximum absolute difference ={res}   .001754
{txt}Iteration 6:  Maximum absolute difference ={res}   .001049
{txt}Iteration 7:  Maximum absolute difference ={res}    .00127
{txt}Iteration 8:  Maximum absolute difference ={res}  .0003028
{txt}Iteration 9:  Maximum absolute difference ={res}  .0001687
{txt}Iteration 10: Maximum absolute difference ={res}  .0001353
{txt}Iteration 11: Maximum absolute difference ={res} .00006517
{txt}Iteration 12: Maximum absolute difference ={res}  .0000208
{txt}Iteration 13: Maximum absolute difference ={res} .00003086
{txt}Iteration 14: Maximum absolute difference ={res} 9.158e-06
{txt}Iteration 15: Maximum absolute difference ={res} 2.331e-06
{txt}Iteration 16: Maximum absolute difference ={res} 5.508e-07
{txt}Iteration 17: Maximum absolute difference ={res} 7.739e-08
{txt}Iteration 18: Maximum absolute difference ={res} 1.363e-08
{txt}Iteration 19: Maximum absolute difference ={res} 1.350e-09

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}    .05072
{txt}Iteration 2:  Maximum absolute difference ={res}     .0215
{txt}Iteration 3:  Maximum absolute difference ={res}    .01512
{txt}Iteration 4:  Maximum absolute difference ={res}   .007332
{txt}Iteration 5:  Maximum absolute difference ={res}   .005705
{txt}Iteration 6:  Maximum absolute difference ={res}   .005201
{txt}Iteration 7:  Maximum absolute difference ={res}   .002405
{txt}Iteration 8:  Maximum absolute difference ={res}  .0006931
{txt}Iteration 9:  Maximum absolute difference ={res}  .0001041
{txt}Iteration 10: Maximum absolute difference ={res} .00008679
{txt}Iteration 11: Maximum absolute difference ={res}  .0001124
{txt}Iteration 12: Maximum absolute difference ={res} .00002002
{txt}Iteration 13: Maximum absolute difference ={res} .00001074
{txt}Iteration 14: Maximum absolute difference ={res} 6.606e-06
{txt}Iteration 15: Maximum absolute difference ={res} 2.641e-06
{txt}Iteration 16: Maximum absolute difference ={res} 1.002e-06
{txt}Iteration 17: Maximum absolute difference ={res} 4.247e-07
{txt}Iteration 18: Maximum absolute difference ={res} 2.650e-08
{txt}Iteration 19: Maximum absolute difference ={res} 4.510e-09

{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 13:Number of obs}{col 66} = {res}{ralign 10:13,989,228}
{txt}{col 53}{lalign 13:Cluster comb.}{col 66} = {res}{ralign 10:3}
{txt}{col 1}Clusters per comb.:{col 53}{lalign 13:F({res:1}, {res:159})}{col 66} = {res}{ralign 10:27.22}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 6:160}{txt}{col 53}{lalign 13:Prob > F}{col 66} = {res}{ralign 10:0.0000}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 6:8,596}{txt}{col 53}{lalign 13:R-squared}{col 66} = {res}{ralign 10:0.4485}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 6:21,610}{txt}{col 53}{lalign 13:Adj R-squared}{col 66} = {res}{ralign 10:0.4463}
{txt}{col 53}{lalign 13:Root MSE}{col 66} = {res}{ralign 10:0.3533}

{txt}{ralign 78:(Std. err. adjusted for multiway clustering)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}againstdem~s{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}leader_cvp {c |}{col 14}{res}{space 2} .4913656{col 26}{space 2} .0941724{col 37}{space 1}    5.22{col 46}{space 3}0.000{col 54}{space 4} .3053754{col 67}{space 3} .6773558
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .2500295{col 26}{space 2} .0181666{col 37}{space 1}   13.76{col 46}{space 3}0.000{col 54}{space 4} .2141504{col 67}{space 3} .2859085
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table1_againstdemocrats.txt", replace 2aster dec(3) sortvar(leader_next leader_cvp leader_prev)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table1_againstdemocrats.txt""':seeout}

{com}. areg againstdemocrats leader_next leader_cvp, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}    .01653
{txt}Iteration 2:  Maximum absolute difference ={res}    .01068
{txt}Iteration 3:  Maximum absolute difference ={res}   .008038
{txt}Iteration 4:  Maximum absolute difference ={res}   .005906
{txt}Iteration 5:  Maximum absolute difference ={res}   .001754
{txt}Iteration 6:  Maximum absolute difference ={res}   .001049
{txt}Iteration 7:  Maximum absolute difference ={res}    .00127
{txt}Iteration 8:  Maximum absolute difference ={res}  .0003028
{txt}Iteration 9:  Maximum absolute difference ={res}  .0001687
{txt}Iteration 10: Maximum absolute difference ={res}  .0001353
{txt}Iteration 11: Maximum absolute difference ={res} .00006517
{txt}Iteration 12: Maximum absolute difference ={res}  .0000208
{txt}Iteration 13: Maximum absolute difference ={res} .00003086
{txt}Iteration 14: Maximum absolute difference ={res} 9.158e-06
{txt}Iteration 15: Maximum absolute difference ={res} 2.331e-06
{txt}Iteration 16: Maximum absolute difference ={res} 5.508e-07
{txt}Iteration 17: Maximum absolute difference ={res} 7.739e-08
{txt}Iteration 18: Maximum absolute difference ={res} 1.363e-08
{txt}Iteration 19: Maximum absolute difference ={res} 1.350e-09

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}    .05072
{txt}Iteration 2:  Maximum absolute difference ={res}     .0215
{txt}Iteration 3:  Maximum absolute difference ={res}    .01512
{txt}Iteration 4:  Maximum absolute difference ={res}   .007332
{txt}Iteration 5:  Maximum absolute difference ={res}   .005705
{txt}Iteration 6:  Maximum absolute difference ={res}   .005201
{txt}Iteration 7:  Maximum absolute difference ={res}   .002405
{txt}Iteration 8:  Maximum absolute difference ={res}  .0007313
{txt}Iteration 9:  Maximum absolute difference ={res}  .0001041
{txt}Iteration 10: Maximum absolute difference ={res} .00008679
{txt}Iteration 11: Maximum absolute difference ={res}  .0001124
{txt}Iteration 12: Maximum absolute difference ={res} .00002002
{txt}Iteration 13: Maximum absolute difference ={res} .00001074
{txt}Iteration 14: Maximum absolute difference ={res} 6.606e-06
{txt}Iteration 15: Maximum absolute difference ={res} 2.641e-06
{txt}Iteration 16: Maximum absolute difference ={res} 1.023e-06
{txt}Iteration 17: Maximum absolute difference ={res} 4.247e-07
{txt}Iteration 18: Maximum absolute difference ={res} 3.087e-08
{txt}Iteration 19: Maximum absolute difference ={res} 8.370e-09

{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 13:Number of obs}{col 66} = {res}{ralign 10:13,989,228}
{txt}{col 53}{lalign 13:Cluster comb.}{col 66} = {res}{ralign 10:3}
{txt}{col 1}Clusters per comb.:{col 53}{lalign 13:F({res:2}, {res:159})}{col 66} = {res}{ralign 10:14.70}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 6:160}{txt}{col 53}{lalign 13:Prob > F}{col 66} = {res}{ralign 10:0.0000}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 6:8,596}{txt}{col 53}{lalign 13:R-squared}{col 66} = {res}{ralign 10:0.4485}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 6:21,610}{txt}{col 53}{lalign 13:Adj R-squared}{col 66} = {res}{ralign 10:0.4463}
{txt}{col 53}{lalign 13:Root MSE}{col 66} = {res}{ralign 10:0.3533}

{txt}{ralign 78:(Std. err. adjusted for multiway clustering)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}againstdem~s{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}leader_next {c |}{col 14}{res}{space 2} .0146371{col 26}{space 2} .1316454{col 37}{space 1}    0.11{col 46}{space 3}0.912{col 54}{space 4}-.2453621{col 67}{space 3} .2746362
{txt}{space 2}leader_cvp {c |}{col 14}{res}{space 2} .4818687{col 26}{space 2} .1417162{col 37}{space 1}    3.40{col 46}{space 3}0.001{col 54}{space 4} .2019798{col 67}{space 3} .7617576
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .2490439{col 26}{space 2} .0181875{col 37}{space 1}   13.69{col 46}{space 3}0.000{col 54}{space 4} .2131236{col 67}{space 3} .2849642
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table1_againstdemocrats.txt", append 2aster dec(3) sortvar(leader_next leader_cvp leader_prev)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table1_againstdemocrats.txt""':seeout}

{com}. areg againstdemocrats leader_next leader_cvp leader_prev, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}    .01653
{txt}Iteration 2:  Maximum absolute difference ={res}    .01068
{txt}Iteration 3:  Maximum absolute difference ={res}   .008038
{txt}Iteration 4:  Maximum absolute difference ={res}   .005906
{txt}Iteration 5:  Maximum absolute difference ={res}   .001754
{txt}Iteration 6:  Maximum absolute difference ={res}   .001049
{txt}Iteration 7:  Maximum absolute difference ={res}    .00127
{txt}Iteration 8:  Maximum absolute difference ={res}  .0003028
{txt}Iteration 9:  Maximum absolute difference ={res}  .0001687
{txt}Iteration 10: Maximum absolute difference ={res}  .0001353
{txt}Iteration 11: Maximum absolute difference ={res} .00006517
{txt}Iteration 12: Maximum absolute difference ={res}  .0000208
{txt}Iteration 13: Maximum absolute difference ={res} .00003086
{txt}Iteration 14: Maximum absolute difference ={res} 9.158e-06
{txt}Iteration 15: Maximum absolute difference ={res} 2.331e-06
{txt}Iteration 16: Maximum absolute difference ={res} 5.508e-07
{txt}Iteration 17: Maximum absolute difference ={res} 7.739e-08
{txt}Iteration 18: Maximum absolute difference ={res} 1.363e-08
{txt}Iteration 19: Maximum absolute difference ={res} 1.350e-09

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}    .05072
{txt}Iteration 2:  Maximum absolute difference ={res}     .0215
{txt}Iteration 3:  Maximum absolute difference ={res}    .01512
{txt}Iteration 4:  Maximum absolute difference ={res}   .008241
{txt}Iteration 5:  Maximum absolute difference ={res}   .005819
{txt}Iteration 6:  Maximum absolute difference ={res}   .006616
{txt}Iteration 7:  Maximum absolute difference ={res}   .002405
{txt}Iteration 8:  Maximum absolute difference ={res}  .0007313
{txt}Iteration 9:  Maximum absolute difference ={res}  .0001232
{txt}Iteration 10: Maximum absolute difference ={res} .00008679
{txt}Iteration 11: Maximum absolute difference ={res}  .0001124
{txt}Iteration 12: Maximum absolute difference ={res} .00002592
{txt}Iteration 13: Maximum absolute difference ={res} .00001074
{txt}Iteration 14: Maximum absolute difference ={res} 6.606e-06
{txt}Iteration 15: Maximum absolute difference ={res} 2.641e-06
{txt}Iteration 16: Maximum absolute difference ={res} 1.023e-06
{txt}Iteration 17: Maximum absolute difference ={res} 4.434e-07
{txt}Iteration 18: Maximum absolute difference ={res} 3.751e-08
{txt}Iteration 19: Maximum absolute difference ={res} 8.370e-09

{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 13:Number of obs}{col 66} = {res}{ralign 10:13,989,228}
{txt}{col 53}{lalign 13:Cluster comb.}{col 66} = {res}{ralign 10:3}
{txt}{col 1}Clusters per comb.:{col 53}{lalign 13:F({res:3}, {res:159})}{col 66} = {res}{ralign 10:19.08}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 6:160}{txt}{col 53}{lalign 13:Prob > F}{col 66} = {res}{ralign 10:0.0000}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 6:8,596}{txt}{col 53}{lalign 13:R-squared}{col 66} = {res}{ralign 10:0.4492}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 6:21,610}{txt}{col 53}{lalign 13:Adj R-squared}{col 66} = {res}{ralign 10:0.4470}
{txt}{col 53}{lalign 13:Root MSE}{col 66} = {res}{ralign 10:0.3531}

{txt}{ralign 78:(Std. err. adjusted for multiway clustering)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}againstdem~s{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}leader_next {c |}{col 14}{res}{space 2} .0263564{col 26}{space 2} .1371037{col 37}{space 1}    0.19{col 46}{space 3}0.848{col 54}{space 4} -.244423{col 67}{space 3} .2971357
{txt}{space 2}leader_cvp {c |}{col 14}{res}{space 2}-.0180755{col 26}{space 2} .1604904{col 37}{space 1}   -0.11{col 46}{space 3}0.910{col 54}{space 4}-.3350435{col 67}{space 3} .2988924
{txt}{space 1}leader_prev {c |}{col 14}{res}{space 2} .6931436{col 26}{space 2} .1351407{col 37}{space 1}    5.13{col 46}{space 3}0.000{col 54}{space 4} .4262412{col 67}{space 3}  .960046
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .2102737{col 26}{space 2} .0188139{col 37}{space 1}   11.18{col 46}{space 3}0.000{col 54}{space 4} .1731164{col 67}{space 3}  .247431
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table1_againstdemocrats.txt", append 2aster dec(3) sortvar(leader_next leader_cvp leader_prev)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table1_againstdemocrats.txt""':seeout}

{com}. areg againstdemocrats leader_cvp leader_cvp_house, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}    .01653
{txt}Iteration 2:  Maximum absolute difference ={res}    .01068
{txt}Iteration 3:  Maximum absolute difference ={res}   .008038
{txt}Iteration 4:  Maximum absolute difference ={res}   .005906
{txt}Iteration 5:  Maximum absolute difference ={res}   .001754
{txt}Iteration 6:  Maximum absolute difference ={res}   .001049
{txt}Iteration 7:  Maximum absolute difference ={res}    .00127
{txt}Iteration 8:  Maximum absolute difference ={res}  .0003028
{txt}Iteration 9:  Maximum absolute difference ={res}  .0001687
{txt}Iteration 10: Maximum absolute difference ={res}  .0001353
{txt}Iteration 11: Maximum absolute difference ={res} .00006517
{txt}Iteration 12: Maximum absolute difference ={res}  .0000208
{txt}Iteration 13: Maximum absolute difference ={res} .00003086
{txt}Iteration 14: Maximum absolute difference ={res} 9.158e-06
{txt}Iteration 15: Maximum absolute difference ={res} 2.331e-06
{txt}Iteration 16: Maximum absolute difference ={res} 5.508e-07
{txt}Iteration 17: Maximum absolute difference ={res} 7.739e-08
{txt}Iteration 18: Maximum absolute difference ={res} 1.363e-08
{txt}Iteration 19: Maximum absolute difference ={res} 1.350e-09

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}    .05072
{txt}Iteration 2:  Maximum absolute difference ={res}     .0215
{txt}Iteration 3:  Maximum absolute difference ={res}    .01512
{txt}Iteration 4:  Maximum absolute difference ={res}   .007332
{txt}Iteration 5:  Maximum absolute difference ={res}   .005705
{txt}Iteration 6:  Maximum absolute difference ={res}   .005201
{txt}Iteration 7:  Maximum absolute difference ={res}   .002405
{txt}Iteration 8:  Maximum absolute difference ={res}  .0006931
{txt}Iteration 9:  Maximum absolute difference ={res}  .0001041
{txt}Iteration 10: Maximum absolute difference ={res} .00008679
{txt}Iteration 11: Maximum absolute difference ={res}  .0001124
{txt}Iteration 12: Maximum absolute difference ={res} .00002002
{txt}Iteration 13: Maximum absolute difference ={res} .00001074
{txt}Iteration 14: Maximum absolute difference ={res} 6.606e-06
{txt}Iteration 15: Maximum absolute difference ={res} 2.641e-06
{txt}Iteration 16: Maximum absolute difference ={res} 1.002e-06
{txt}Iteration 17: Maximum absolute difference ={res} 4.247e-07
{txt}Iteration 18: Maximum absolute difference ={res} 2.650e-08
{txt}Iteration 19: Maximum absolute difference ={res} 4.510e-09

{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 13:Number of obs}{col 66} = {res}{ralign 10:13,989,228}
{txt}{col 53}{lalign 13:Cluster comb.}{col 66} = {res}{ralign 10:3}
{txt}{col 1}Clusters per comb.:{col 53}{lalign 13:F({res:2}, {res:159})}{col 66} = {res}{ralign 10:15.90}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 6:160}{txt}{col 53}{lalign 13:Prob > F}{col 66} = {res}{ralign 10:0.0000}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 6:8,596}{txt}{col 53}{lalign 13:R-squared}{col 66} = {res}{ralign 10:0.4488}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 6:21,610}{txt}{col 53}{lalign 13:Adj R-squared}{col 66} = {res}{ralign 10:0.4465}
{txt}{col 53}{lalign 13:Root MSE}{col 66} = {res}{ralign 10:0.3532}

{txt}{ralign 82:(Std. err. adjusted for multiway clustering)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}againstdemocrats{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}leader_cvp {c |}{col 18}{res}{space 2} .1865479{col 30}{space 2} .0654483{col 41}{space 1}    2.85{col 50}{space 3}0.005{col 58}{space 4} .0572878{col 71}{space 3} .3158081
{txt}leader_cvp_house {c |}{col 18}{res}{space 2} .5923614{col 30}{space 2} .1729451{col 41}{space 1}    3.43{col 50}{space 3}0.001{col 58}{space 4} .2507956{col 71}{space 3} .9339273
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .1968711{col 30}{space 2} .0302493{col 41}{space 1}    6.51{col 50}{space 3}0.000{col 58}{space 4} .1371288{col 71}{space 3} .2566135
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table1_againstdemocrats.txt", append 2aster dec(3) sortvar(leader_next leader_cvp leader_prev)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table1_againstdemocrats.txt""':seeout}

{com}. areg againstdemocrats leader_cvp leader_cvp_dem, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}    .01653
{txt}Iteration 2:  Maximum absolute difference ={res}    .01068
{txt}Iteration 3:  Maximum absolute difference ={res}   .008038
{txt}Iteration 4:  Maximum absolute difference ={res}   .005906
{txt}Iteration 5:  Maximum absolute difference ={res}   .001754
{txt}Iteration 6:  Maximum absolute difference ={res}   .001049
{txt}Iteration 7:  Maximum absolute difference ={res}    .00127
{txt}Iteration 8:  Maximum absolute difference ={res}  .0003028
{txt}Iteration 9:  Maximum absolute difference ={res}  .0001687
{txt}Iteration 10: Maximum absolute difference ={res}  .0001353
{txt}Iteration 11: Maximum absolute difference ={res} .00006517
{txt}Iteration 12: Maximum absolute difference ={res}  .0000208
{txt}Iteration 13: Maximum absolute difference ={res} .00003086
{txt}Iteration 14: Maximum absolute difference ={res} 9.158e-06
{txt}Iteration 15: Maximum absolute difference ={res} 2.331e-06
{txt}Iteration 16: Maximum absolute difference ={res} 5.508e-07
{txt}Iteration 17: Maximum absolute difference ={res} 7.739e-08
{txt}Iteration 18: Maximum absolute difference ={res} 1.363e-08
{txt}Iteration 19: Maximum absolute difference ={res} 1.350e-09

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}    .05072
{txt}Iteration 2:  Maximum absolute difference ={res}     .0215
{txt}Iteration 3:  Maximum absolute difference ={res}    .01512
{txt}Iteration 4:  Maximum absolute difference ={res}   .007332
{txt}Iteration 5:  Maximum absolute difference ={res}   .005705
{txt}Iteration 6:  Maximum absolute difference ={res}   .005201
{txt}Iteration 7:  Maximum absolute difference ={res}   .002405
{txt}Iteration 8:  Maximum absolute difference ={res}   .001053
{txt}Iteration 9:  Maximum absolute difference ={res}  .0001041
{txt}Iteration 10: Maximum absolute difference ={res} .00008679
{txt}Iteration 11: Maximum absolute difference ={res}  .0001124
{txt}Iteration 12: Maximum absolute difference ={res} .00002002
{txt}Iteration 13: Maximum absolute difference ={res} .00001074
{txt}Iteration 14: Maximum absolute difference ={res} 6.606e-06
{txt}Iteration 15: Maximum absolute difference ={res} 2.641e-06
{txt}Iteration 16: Maximum absolute difference ={res} 1.002e-06
{txt}Iteration 17: Maximum absolute difference ={res} 4.247e-07
{txt}Iteration 18: Maximum absolute difference ={res} 2.650e-08
{txt}Iteration 19: Maximum absolute difference ={res} 4.510e-09

{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 13:Number of obs}{col 66} = {res}{ralign 10:13,989,228}
{txt}{col 53}{lalign 13:Cluster comb.}{col 66} = {res}{ralign 10:3}
{txt}{col 1}Clusters per comb.:{col 53}{lalign 13:F({res:2}, {res:159})}{col 66} = {res}{ralign 10:16.77}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 6:160}{txt}{col 53}{lalign 13:Prob > F}{col 66} = {res}{ralign 10:0.0000}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 6:8,596}{txt}{col 53}{lalign 13:R-squared}{col 66} = {res}{ralign 10:0.4485}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 6:21,610}{txt}{col 53}{lalign 13:Adj R-squared}{col 66} = {res}{ralign 10:0.4463}
{txt}{col 53}{lalign 13:Root MSE}{col 66} = {res}{ralign 10:0.3533}

{txt}{ralign 80:(Std. err. adjusted for multiway clustering)}
{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}againstdemoc~s{col 16}{c |} Coefficient{col 28}  std. err.{col 40}      t{col 48}   P>|t|{col 56}     [95% con{col 69}f. interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}leader_cvp {c |}{col 16}{res}{space 2}  .518611{col 28}{space 2} .0970558{col 39}{space 1}    5.34{col 48}{space 3}0.000{col 56}{space 4} .3269261{col 69}{space 3} .7102958
{txt}leader_cvp_dem {c |}{col 16}{res}{space 2}-.0740475{col 28}{space 2} .2188509{col 39}{space 1}   -0.34{col 48}{space 3}0.736{col 56}{space 4}-.5062771{col 69}{space 3} .3581822
{txt}{space 9}_cons {c |}{col 16}{res}{space 2} .2413857{col 28}{space 2} .0249632{col 39}{space 1}    9.67{col 48}{space 3}0.000{col 56}{space 4} .1920835{col 69}{space 3} .2906879
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table1_againstdemocrats.txt", append 2aster dec(3) sortvar(leader_next leader_cvp leader_prev)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table1_againstdemocrats.txt""':seeout}

{com}. areg againstdemocrats leader_cvp leader_cvp_majority, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}    .01653
{txt}Iteration 2:  Maximum absolute difference ={res}    .01068
{txt}Iteration 3:  Maximum absolute difference ={res}   .008038
{txt}Iteration 4:  Maximum absolute difference ={res}   .005906
{txt}Iteration 5:  Maximum absolute difference ={res}   .001754
{txt}Iteration 6:  Maximum absolute difference ={res}   .001049
{txt}Iteration 7:  Maximum absolute difference ={res}    .00127
{txt}Iteration 8:  Maximum absolute difference ={res}  .0003028
{txt}Iteration 9:  Maximum absolute difference ={res}  .0001687
{txt}Iteration 10: Maximum absolute difference ={res}  .0001353
{txt}Iteration 11: Maximum absolute difference ={res} .00006517
{txt}Iteration 12: Maximum absolute difference ={res}  .0000208
{txt}Iteration 13: Maximum absolute difference ={res} .00003086
{txt}Iteration 14: Maximum absolute difference ={res} 9.158e-06
{txt}Iteration 15: Maximum absolute difference ={res} 2.331e-06
{txt}Iteration 16: Maximum absolute difference ={res} 5.508e-07
{txt}Iteration 17: Maximum absolute difference ={res} 7.739e-08
{txt}Iteration 18: Maximum absolute difference ={res} 1.363e-08
{txt}Iteration 19: Maximum absolute difference ={res} 1.350e-09

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}     .1015
{txt}Iteration 2:  Maximum absolute difference ={res}    .05568
{txt}Iteration 3:  Maximum absolute difference ={res}    .05893
{txt}Iteration 4:  Maximum absolute difference ={res}    .02669
{txt}Iteration 5:  Maximum absolute difference ={res}    .05127
{txt}Iteration 6:  Maximum absolute difference ={res}    .02269
{txt}Iteration 7:  Maximum absolute difference ={res}   .007504
{txt}Iteration 8:  Maximum absolute difference ={res}   .004196
{txt}Iteration 9:  Maximum absolute difference ={res}   .001672
{txt}Iteration 10: Maximum absolute difference ={res}   .001032
{txt}Iteration 11: Maximum absolute difference ={res}  .0004369
{txt}Iteration 12: Maximum absolute difference ={res}  .0003134
{txt}Iteration 13: Maximum absolute difference ={res}  .0002368
{txt}Iteration 14: Maximum absolute difference ={res}  .0000242
{txt}Iteration 15: Maximum absolute difference ={res} 4.047e-06
{txt}Iteration 16: Maximum absolute difference ={res} 1.002e-06
{txt}Iteration 17: Maximum absolute difference ={res} 4.247e-07
{txt}Iteration 18: Maximum absolute difference ={res} 2.941e-08
{txt}Iteration 19: Maximum absolute difference ={res} 4.510e-09

{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 13:Number of obs}{col 66} = {res}{ralign 10:13,989,228}
{txt}{col 53}{lalign 13:Cluster comb.}{col 66} = {res}{ralign 10:3}
{txt}{col 1}Clusters per comb.:{col 53}{lalign 13:F({res:2}, {res:159})}{col 66} = {res}{ralign 10:14.41}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 6:160}{txt}{col 53}{lalign 13:Prob > F}{col 66} = {res}{ralign 10:0.0000}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 6:8,596}{txt}{col 53}{lalign 13:R-squared}{col 66} = {res}{ralign 10:0.4486}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 6:21,610}{txt}{col 53}{lalign 13:Adj R-squared}{col 66} = {res}{ralign 10:0.4464}
{txt}{col 53}{lalign 13:Root MSE}{col 66} = {res}{ralign 10:0.3532}

{txt}{ralign 85:(Std. err. adjusted for multiway clustering)}
{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}   againstdemocrats{col 21}{c |} Coefficient{col 33}  std. err.{col 45}      t{col 53}   P>|t|{col 61}     [95% con{col 74}f. interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}leader_cvp {c |}{col 21}{res}{space 2} .5170546{col 33}{space 2} .0972872{col 44}{space 1}    5.31{col 53}{space 3}0.000{col 61}{space 4} .3249128{col 74}{space 3} .7091964
{txt}leader_cvp_majority {c |}{col 21}{res}{space 2}-.0536772{col 33}{space 2}  .035783{col 44}{space 1}   -1.50{col 53}{space 3}0.136{col 61}{space 4}-.1243485{col 74}{space 3} .0169942
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} .2495797{col 33}{space 2} .0177035{col 44}{space 1}   14.10{col 53}{space 3}0.000{col 61}{space 4} .2146154{col 74}{space 3}  .284544
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table1_againstdemocrats.txt", append 2aster dec(3) sortvar(leader_next leader_cvp leader_prev)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table1_againstdemocrats.txt""':seeout}

{com}. areg againstdemocrats leader_cvp leader_cvp_moderate, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}    .01653
{txt}Iteration 2:  Maximum absolute difference ={res}    .01068
{txt}Iteration 3:  Maximum absolute difference ={res}   .008038
{txt}Iteration 4:  Maximum absolute difference ={res}   .005906
{txt}Iteration 5:  Maximum absolute difference ={res}   .001754
{txt}Iteration 6:  Maximum absolute difference ={res}   .001049
{txt}Iteration 7:  Maximum absolute difference ={res}    .00127
{txt}Iteration 8:  Maximum absolute difference ={res}  .0003028
{txt}Iteration 9:  Maximum absolute difference ={res}  .0001687
{txt}Iteration 10: Maximum absolute difference ={res}  .0001353
{txt}Iteration 11: Maximum absolute difference ={res} .00006517
{txt}Iteration 12: Maximum absolute difference ={res}  .0000208
{txt}Iteration 13: Maximum absolute difference ={res} .00003086
{txt}Iteration 14: Maximum absolute difference ={res} 9.158e-06
{txt}Iteration 15: Maximum absolute difference ={res} 2.331e-06
{txt}Iteration 16: Maximum absolute difference ={res} 5.508e-07
{txt}Iteration 17: Maximum absolute difference ={res} 7.739e-08
{txt}Iteration 18: Maximum absolute difference ={res} 1.363e-08
{txt}Iteration 19: Maximum absolute difference ={res} 1.350e-09

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}    .05072
{txt}Iteration 2:  Maximum absolute difference ={res}     .0215
{txt}Iteration 3:  Maximum absolute difference ={res}    .01512
{txt}Iteration 4:  Maximum absolute difference ={res}   .007332
{txt}Iteration 5:  Maximum absolute difference ={res}   .005705
{txt}Iteration 6:  Maximum absolute difference ={res}   .005201
{txt}Iteration 7:  Maximum absolute difference ={res}   .002405
{txt}Iteration 8:  Maximum absolute difference ={res}  .0006931
{txt}Iteration 9:  Maximum absolute difference ={res}  .0001041
{txt}Iteration 10: Maximum absolute difference ={res}  .0001422
{txt}Iteration 11: Maximum absolute difference ={res}  .0001124
{txt}Iteration 12: Maximum absolute difference ={res} .00002002
{txt}Iteration 13: Maximum absolute difference ={res} .00001074
{txt}Iteration 14: Maximum absolute difference ={res} 6.606e-06
{txt}Iteration 15: Maximum absolute difference ={res} 2.641e-06
{txt}Iteration 16: Maximum absolute difference ={res} 1.002e-06
{txt}Iteration 17: Maximum absolute difference ={res} 4.247e-07
{txt}Iteration 18: Maximum absolute difference ={res} 2.650e-08
{txt}Iteration 19: Maximum absolute difference ={res} 4.510e-09

{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 13:Number of obs}{col 66} = {res}{ralign 10:13,989,228}
{txt}{col 53}{lalign 13:Cluster comb.}{col 66} = {res}{ralign 10:3}
{txt}{col 1}Clusters per comb.:{col 53}{lalign 13:F({res:2}, {res:159})}{col 66} = {res}{ralign 10:15.89}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 6:160}{txt}{col 53}{lalign 13:Prob > F}{col 66} = {res}{ralign 10:0.0000}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 6:8,596}{txt}{col 53}{lalign 13:R-squared}{col 66} = {res}{ralign 10:0.4485}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 6:21,610}{txt}{col 53}{lalign 13:Adj R-squared}{col 66} = {res}{ralign 10:0.4463}
{txt}{col 53}{lalign 13:Root MSE}{col 66} = {res}{ralign 10:0.3533}

{txt}{ralign 85:(Std. err. adjusted for multiway clustering)}
{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}   againstdemocrats{col 21}{c |} Coefficient{col 33}  std. err.{col 45}      t{col 53}   P>|t|{col 61}     [95% con{col 74}f. interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}leader_cvp {c |}{col 21}{res}{space 2} .4564774{col 33}{space 2} .1054157{col 44}{space 1}    4.33{col 53}{space 3}0.000{col 61}{space 4} .2482818{col 74}{space 3} .6646729
{txt}leader_cvp_moderate {c |}{col 21}{res}{space 2} .0686046{col 33}{space 2} .0635449{col 44}{space 1}    1.08{col 53}{space 3}0.282{col 61}{space 4}-.0568963{col 74}{space 3} .1941055
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} .2503121{col 33}{space 2} .0182262{col 44}{space 1}   13.73{col 53}{space 3}0.000{col 61}{space 4} .2143155{col 74}{space 3} .2863088
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table1_againstdemocrats.txt", append 2aster dec(3) sortvar(leader_next leader_cvp leader_prev)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table1_againstdemocrats.txt""':seeout}

{com}. 
. 
. *Table 2
. clear
{txt}
{com}. use "CleanedRollCallData.dta"
{txt}
{com}. keep if house == 1
{txt}(2,115,545 observations deleted)

{com}. *focus on Congresses 87-91, where the only leader change in either party was from Halleck to Ford
. keep if congress >= 87 & congress <= 91
{txt}(11,846,786 observations deleted)

{com}. *keep only members who served under both Halleck and Ford
. egen mincong = min(congress), by(member_party_chamber)
{txt}
{com}. egen maxcong = max(congress), by(member_party_chamber)
{txt}
{com}. keep if mincong <= 88 & maxcong >= 89
{txt}(177,334 observations deleted)

{com}. merge m:1 icpsr using "fordvotes.dta"
{res}
{txt}{col 5}Result{col 33}Number of obs
{col 5}{hline 41}
{col 5}Not matched{col 30}{res}         285,855
{txt}{col 9}from master{col 30}{res}         285,832{txt}  (_merge==1)
{col 9}from using{col 30}{res}              23{txt}  (_merge==2)

{col 5}Matched{col 30}{res}         151,861{txt}  (_merge==3)
{col 5}{hline 41}

{com}. replace fordvote1 = 0 if fordvote1 == .
{txt}(285,832 real changes made)

{com}. replace fordvote2 = 0 if fordvote2 == .
{txt}(285,832 real changes made)

{com}. g fordleadership = dem == 0 & congress >= 89
{txt}
{com}. g ford_ford1 = fordleadership*fordvote1
{txt}
{com}. g ford_ford2 = fordleadership*fordvote2
{txt}
{com}. 
. areg conservative fordleadership, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}   .005706
{txt}Iteration 2:  Maximum absolute difference ={res}  .0001518
{txt}Iteration 3:  Maximum absolute difference ={res} 2.380e-06
{txt}Iteration 4:  Maximum absolute difference ={res} 1.172e-08
{txt}Iteration 5:  Maximum absolute difference ={res} 9.077e-11

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}    .02583
{txt}Iteration 2:  Maximum absolute difference ={res}  .0003896
{txt}Iteration 3:  Maximum absolute difference ={res} 5.587e-06
{txt}Iteration 4:  Maximum absolute difference ={res} 1.820e-08
{txt}Iteration 5:  Maximum absolute difference ={res} 1.509e-10

{txt}{col 1}Linear regression, absorbing indicators{col 56}{lalign 13:Number of obs}{col 69} = {res}{ralign 7:437,693}
{txt}{col 56}{lalign 13:Cluster comb.}{col 69} = {res}{ralign 7:3}
{txt}{col 1}Clusters per comb.:{col 56}{lalign 13:F({res:1}, {res:9})}{col 69} = {res}{ralign 7:22.05}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 5:10}{txt}{col 56}{lalign 13:Prob > F}{col 69} = {res}{ralign 7:0.0011}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 5:643}{txt}{col 56}{lalign 13:R-squared}{col 69} = {res}{ralign 7:0.5042}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 5:1,564}{txt}{col 56}{lalign 13:Adj R-squared}{col 69} = {res}{ralign 7:0.5019}
{txt}{col 56}{lalign 13:Root MSE}{col 69} = {res}{ralign 7:0.3456}

{txt}{ralign 80:(Std. err. adjusted for multiway clustering)}
{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}  conservative{col 16}{c |} Coefficient{col 28}  std. err.{col 40}      t{col 48}   P>|t|{col 56}     [95% con{col 69}f. interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
fordleadership {c |}{col 16}{res}{space 2}-.1374549{col 28}{space 2} .0292742{col 39}{space 1}   -4.70{col 48}{space 3}0.001{col 56}{space 4}-.2036777{col 69}{space 3}-.0712322
{txt}{space 9}_cons {c |}{col 16}{res}{space 2} .4356329{col 28}{space 2}  .010398{col 39}{space 1}   41.90{col 48}{space 3}0.000{col 56}{space 4}  .412111{col 69}{space 3} .4591548
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table2_conservative.txt", replace 2aster dec(3)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table2_conservative.txt""':seeout}

{com}. areg conservative fordleadership ford_ford1, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}   .005706
{txt}Iteration 2:  Maximum absolute difference ={res}  .0001518
{txt}Iteration 3:  Maximum absolute difference ={res} 2.380e-06
{txt}Iteration 4:  Maximum absolute difference ={res} 1.172e-08
{txt}Iteration 5:  Maximum absolute difference ={res} 9.077e-11

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}    .02583
{txt}Iteration 2:  Maximum absolute difference ={res}  .0003896
{txt}Iteration 3:  Maximum absolute difference ={res} 5.587e-06
{txt}Iteration 4:  Maximum absolute difference ={res} 1.820e-08
{txt}Iteration 5:  Maximum absolute difference ={res} 1.509e-10

{txt}{col 1}Linear regression, absorbing indicators{col 56}{lalign 13:Number of obs}{col 69} = {res}{ralign 7:437,693}
{txt}{col 56}{lalign 13:Cluster comb.}{col 69} = {res}{ralign 7:3}
{txt}{col 1}Clusters per comb.:{col 56}{lalign 13:F({res:2}, {res:9})}{col 69} = {res}{ralign 7:11.58}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 5:10}{txt}{col 56}{lalign 13:Prob > F}{col 69} = {res}{ralign 7:0.0032}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 5:643}{txt}{col 56}{lalign 13:R-squared}{col 69} = {res}{ralign 7:0.5042}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 5:1,564}{txt}{col 56}{lalign 13:Adj R-squared}{col 69} = {res}{ralign 7:0.5019}
{txt}{col 56}{lalign 13:Root MSE}{col 69} = {res}{ralign 7:0.3456}

{txt}{ralign 80:(Std. err. adjusted for multiway clustering)}
{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}  conservative{col 16}{c |} Coefficient{col 28}  std. err.{col 40}      t{col 48}   P>|t|{col 56}     [95% con{col 69}f. interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
fordleadership {c |}{col 16}{res}{space 2}-.1373436{col 28}{space 2} .0303307{col 39}{space 1}   -4.53{col 48}{space 3}0.001{col 56}{space 4}-.2059565{col 69}{space 3}-.0687307
{txt}{space 4}ford_ford1 {c |}{col 16}{res}{space 2}-.0002447{col 28}{space 2} .0084566{col 39}{space 1}   -0.03{col 48}{space 3}0.978{col 56}{space 4}-.0193749{col 69}{space 3} .0188855
{txt}{space 9}_cons {c |}{col 16}{res}{space 2} .4356331{col 28}{space 2} .0103984{col 39}{space 1}   41.89{col 48}{space 3}0.000{col 56}{space 4} .4121101{col 69}{space 3}  .459156
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table2_conservative.txt", append 2aster dec(3)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table2_conservative.txt""':seeout}

{com}. areg conservative fordleadership ford_ford2, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}   .005706
{txt}Iteration 2:  Maximum absolute difference ={res}  .0001518
{txt}Iteration 3:  Maximum absolute difference ={res} 2.380e-06
{txt}Iteration 4:  Maximum absolute difference ={res} 1.172e-08
{txt}Iteration 5:  Maximum absolute difference ={res} 9.077e-11

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}    .02583
{txt}Iteration 2:  Maximum absolute difference ={res}  .0003896
{txt}Iteration 3:  Maximum absolute difference ={res} 5.587e-06
{txt}Iteration 4:  Maximum absolute difference ={res} 1.820e-08
{txt}Iteration 5:  Maximum absolute difference ={res} 1.509e-10

{txt}{col 1}Linear regression, absorbing indicators{col 56}{lalign 13:Number of obs}{col 69} = {res}{ralign 7:437,693}
{txt}{col 56}{lalign 13:Cluster comb.}{col 69} = {res}{ralign 7:3}
{txt}{col 1}Clusters per comb.:{col 56}{lalign 13:F({res:2}, {res:9})}{col 69} = {res}{ralign 7:11.02}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 5:10}{txt}{col 56}{lalign 13:Prob > F}{col 69} = {res}{ralign 7:0.0038}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 5:643}{txt}{col 56}{lalign 13:R-squared}{col 69} = {res}{ralign 7:0.5042}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 5:1,564}{txt}{col 56}{lalign 13:Adj R-squared}{col 69} = {res}{ralign 7:0.5019}
{txt}{col 56}{lalign 13:Root MSE}{col 69} = {res}{ralign 7:0.3456}

{txt}{ralign 80:(Std. err. adjusted for multiway clustering)}
{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}  conservative{col 16}{c |} Coefficient{col 28}  std. err.{col 40}      t{col 48}   P>|t|{col 56}     [95% con{col 69}f. interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
fordleadership {c |}{col 16}{res}{space 2}-.1362603{col 28}{space 2} .0293423{col 39}{space 1}   -4.64{col 48}{space 3}0.001{col 56}{space 4}-.2026371{col 69}{space 3}-.0698834
{txt}{space 4}ford_ford2 {c |}{col 16}{res}{space 2} -.002312{col 28}{space 2} .0096563{col 39}{space 1}   -0.24{col 48}{space 3}0.816{col 56}{space 4} -.024156{col 69}{space 3}  .019532
{txt}{space 9}_cons {c |}{col 16}{res}{space 2} .4356352{col 28}{space 2} .0104015{col 39}{space 1}   41.88{col 48}{space 3}0.000{col 56}{space 4} .4121053{col 69}{space 3}  .459165
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table2_conservative.txt", append 2aster dec(3)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table2_conservative.txt""':seeout}

{com}. areg conservative fordleadership if congress >= 88 & congress <= 89, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}   .002464
{txt}Iteration 2:  Maximum absolute difference ={res} .00004762
{txt}Iteration 3:  Maximum absolute difference ={res} 7.956e-08
{txt}Iteration 4:  Maximum absolute difference ={res} 2.627e-10

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}    .01221
{txt}Iteration 2:  Maximum absolute difference ={res} .00002347
{txt}Iteration 3:  Maximum absolute difference ={res} 7.028e-08
{txt}Iteration 4:  Maximum absolute difference ={res} 7.454e-11
{txt}{p 0 6 2}note: multiway-cluster variance{ch_endash}covariance {helpb j_cluster_multiway_pd:matrix} is not positive semidefinite.{p_end}

{col 1}Linear regression, absorbing indicators{col 56}{lalign 13:Number of obs}{col 69} = {res}{ralign 7:173,956}
{txt}{col 56}{lalign 13:Cluster comb.}{col 69} = {res}{ralign 7:3}
{txt}{col 1}Clusters per comb.:{col 56}{lalign 13:F({res:1}, {res:3})}{col 69} = {res}{ralign 7:132.57}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 3:4}{txt}{col 56}{lalign 13:Prob > F}{col 69} = {res}{ralign 7:0.0014}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 3:351}{txt}{col 56}{lalign 13:R-squared}{col 69} = {res}{ralign 7:0.5104}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 3:694}{txt}{col 56}{lalign 13:Adj R-squared}{col 69} = {res}{ralign 7:0.5078}
{txt}{col 56}{lalign 13:Root MSE}{col 69} = {res}{ralign 7:0.3409}

{txt}{ralign 80:(Std. err. adjusted for multiway clustering)}
{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}  conservative{col 16}{c |} Coefficient{col 28}  std. err.{col 40}      t{col 48}   P>|t|{col 56}     [95% con{col 69}f. interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
fordleadership {c |}{col 16}{res}{space 2}-.0529386{col 28}{space 2} .0045978{col 39}{space 1}  -11.51{col 48}{space 3}0.001{col 56}{space 4}-.0675707{col 69}{space 3}-.0383064
{txt}{space 9}_cons {c |}{col 16}{res}{space 2} .3930863{col 28}{space 2} .0009693{col 39}{space 1}  405.52{col 48}{space 3}0.000{col 56}{space 4} .3900015{col 69}{space 3} .3961712
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table2_conservative.txt", append 2aster dec(3)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table2_conservative.txt""':seeout}

{com}. areg conservative fordleadership ford_ford1 if congress >= 88 & congress <= 89, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}   .002464
{txt}Iteration 2:  Maximum absolute difference ={res} .00004762
{txt}Iteration 3:  Maximum absolute difference ={res} 7.956e-08
{txt}Iteration 4:  Maximum absolute difference ={res} 2.627e-10

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}    .01221
{txt}Iteration 2:  Maximum absolute difference ={res} .00002347
{txt}Iteration 3:  Maximum absolute difference ={res} 7.028e-08
{txt}Iteration 4:  Maximum absolute difference ={res} 7.454e-11
{txt}{p 0 6 2}note: multiway-cluster variance{ch_endash}covariance {helpb j_cluster_multiway_pd:matrix} is not positive semidefinite.{p_end}

{col 1}Linear regression, absorbing indicators{col 56}{lalign 13:Number of obs}{col 69} = {res}{ralign 7:173,956}
{txt}{col 56}{lalign 13:Cluster comb.}{col 69} = {res}{ralign 7:3}
{txt}{col 1}Clusters per comb.:{col 56}{lalign 13:F({res:2}, {res:3})}{col 69} = {res}{ralign 7:67.70}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 3:4}{txt}{col 56}{lalign 13:Prob > F}{col 69} = {res}{ralign 7:0.0032}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 3:351}{txt}{col 56}{lalign 13:R-squared}{col 69} = {res}{ralign 7:0.5104}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 3:694}{txt}{col 56}{lalign 13:Adj R-squared}{col 69} = {res}{ralign 7:0.5078}
{txt}{col 56}{lalign 13:Root MSE}{col 69} = {res}{ralign 7:0.3409}

{txt}{ralign 80:(Std. err. adjusted for multiway clustering)}
{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}  conservative{col 16}{c |} Coefficient{col 28}  std. err.{col 40}      t{col 48}   P>|t|{col 56}     [95% con{col 69}f. interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
fordleadership {c |}{col 16}{res}{space 2}-.0467663{col 28}{space 2} .0054762{col 39}{space 1}   -8.54{col 48}{space 3}0.003{col 56}{space 4}-.0641938{col 69}{space 3}-.0293387
{txt}{space 4}ford_ford1 {c |}{col 16}{res}{space 2}-.0122786{col 28}{space 2} .0065128{col 39}{space 1}   -1.89{col 48}{space 3}0.156{col 56}{space 4}-.0330051{col 69}{space 3}  .008448
{txt}{space 9}_cons {c |}{col 16}{res}{space 2} .3930999{col 28}{space 2} .0009549{col 39}{space 1}  411.65{col 48}{space 3}0.000{col 56}{space 4} .3900608{col 69}{space 3} .3961389
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table2_conservative.txt", append 2aster dec(3)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table2_conservative.txt""':seeout}

{com}. areg conservative fordleadership ford_ford2 if congress >= 88 & congress <= 89, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}   .002464
{txt}Iteration 2:  Maximum absolute difference ={res} .00004762
{txt}Iteration 3:  Maximum absolute difference ={res} 7.956e-08
{txt}Iteration 4:  Maximum absolute difference ={res} 2.627e-10

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}    .01221
{txt}Iteration 2:  Maximum absolute difference ={res} .00002347
{txt}Iteration 3:  Maximum absolute difference ={res} 7.028e-08
{txt}Iteration 4:  Maximum absolute difference ={res} 7.454e-11
{txt}{p 0 6 2}note: multiway-cluster variance{ch_endash}covariance {helpb j_cluster_multiway_pd:matrix} is not positive semidefinite.{p_end}

{col 1}Linear regression, absorbing indicators{col 56}{lalign 13:Number of obs}{col 69} = {res}{ralign 7:173,956}
{txt}{col 56}{lalign 13:Cluster comb.}{col 69} = {res}{ralign 7:3}
{txt}{col 1}Clusters per comb.:{col 56}{lalign 13:F({res:2}, {res:3})}{col 69} = {res}{ralign 7:66.40}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 3:4}{txt}{col 56}{lalign 13:Prob > F}{col 69} = {res}{ralign 7:0.0033}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 3:351}{txt}{col 56}{lalign 13:R-squared}{col 69} = {res}{ralign 7:0.5104}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 3:694}{txt}{col 56}{lalign 13:Adj R-squared}{col 69} = {res}{ralign 7:0.5078}
{txt}{col 56}{lalign 13:Root MSE}{col 69} = {res}{ralign 7:0.3409}

{txt}{ralign 80:(Std. err. adjusted for multiway clustering)}
{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}  conservative{col 16}{c |} Coefficient{col 28}  std. err.{col 40}      t{col 48}   P>|t|{col 56}     [95% con{col 69}f. interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
fordleadership {c |}{col 16}{res}{space 2}-.0498222{col 28}{space 2} .0057794{col 39}{space 1}   -8.62{col 48}{space 3}0.003{col 56}{space 4}-.0682149{col 69}{space 3}-.0314295
{txt}{space 4}ford_ford2 {c |}{col 16}{res}{space 2}-.0055196{col 28}{space 2} .0067553{col 39}{space 1}   -0.82{col 48}{space 3}0.474{col 56}{space 4}-.0270181{col 69}{space 3}  .015979
{txt}{space 9}_cons {c |}{col 16}{res}{space 2} .3930926{col 28}{space 2}  .000955{col 39}{space 1}  411.62{col 48}{space 3}0.000{col 56}{space 4} .3900534{col 69}{space 3} .3961318
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table2_conservative.txt", append 2aster dec(3)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table2_conservative.txt""':seeout}

{com}. 
. areg reppartyvote fordleadership, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}    .00738
{txt}Iteration 2:  Maximum absolute difference ={res}  .0001316
{txt}Iteration 3:  Maximum absolute difference ={res} 2.103e-06
{txt}Iteration 4:  Maximum absolute difference ={res} 1.316e-08
{txt}Iteration 5:  Maximum absolute difference ={res} 9.449e-11

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}    .02583
{txt}Iteration 2:  Maximum absolute difference ={res}  .0003896
{txt}Iteration 3:  Maximum absolute difference ={res} 5.587e-06
{txt}Iteration 4:  Maximum absolute difference ={res} 1.820e-08
{txt}Iteration 5:  Maximum absolute difference ={res} 1.509e-10

{txt}{col 1}Linear regression, absorbing indicators{col 56}{lalign 13:Number of obs}{col 69} = {res}{ralign 7:437,693}
{txt}{col 56}{lalign 13:Cluster comb.}{col 69} = {res}{ralign 7:3}
{txt}{col 1}Clusters per comb.:{col 56}{lalign 13:F({res:1}, {res:9})}{col 69} = {res}{ralign 7:22.13}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 5:10}{txt}{col 56}{lalign 13:Prob > F}{col 69} = {res}{ralign 7:0.0011}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 5:643}{txt}{col 56}{lalign 13:R-squared}{col 69} = {res}{ralign 7:0.4974}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 5:1,564}{txt}{col 56}{lalign 13:Adj R-squared}{col 69} = {res}{ralign 7:0.4951}
{txt}{col 56}{lalign 13:Root MSE}{col 69} = {res}{ralign 7:0.3529}

{txt}{ralign 80:(Std. err. adjusted for multiway clustering)}
{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}  reppartyvote{col 16}{c |} Coefficient{col 28}  std. err.{col 40}      t{col 48}   P>|t|{col 56}     [95% con{col 69}f. interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
fordleadership {c |}{col 16}{res}{space 2}-.1285094{col 28}{space 2} .0273182{col 39}{space 1}   -4.70{col 48}{space 3}0.001{col 56}{space 4}-.1903074{col 69}{space 3}-.0667114
{txt}{space 9}_cons {c |}{col 16}{res}{space 2} .4762976{col 28}{space 2} .0096999{col 39}{space 1}   49.10{col 48}{space 3}0.000{col 56}{space 4} .4543549{col 69}{space 3} .4982403
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table2_republicandirection.txt", replace 2aster dec(3)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table2_republicandirection.txt""':seeout}

{com}. areg reppartyvote fordleadership ford_ford1, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}    .00738
{txt}Iteration 2:  Maximum absolute difference ={res}  .0001316
{txt}Iteration 3:  Maximum absolute difference ={res} 2.103e-06
{txt}Iteration 4:  Maximum absolute difference ={res} 1.316e-08
{txt}Iteration 5:  Maximum absolute difference ={res} 9.449e-11

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}    .02583
{txt}Iteration 2:  Maximum absolute difference ={res}  .0003896
{txt}Iteration 3:  Maximum absolute difference ={res} 5.587e-06
{txt}Iteration 4:  Maximum absolute difference ={res} 1.820e-08
{txt}Iteration 5:  Maximum absolute difference ={res} 1.509e-10

{txt}{col 1}Linear regression, absorbing indicators{col 56}{lalign 13:Number of obs}{col 69} = {res}{ralign 7:437,693}
{txt}{col 56}{lalign 13:Cluster comb.}{col 69} = {res}{ralign 7:3}
{txt}{col 1}Clusters per comb.:{col 56}{lalign 13:F({res:2}, {res:9})}{col 69} = {res}{ralign 7:12.68}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 5:10}{txt}{col 56}{lalign 13:Prob > F}{col 69} = {res}{ralign 7:0.0024}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 5:643}{txt}{col 56}{lalign 13:R-squared}{col 69} = {res}{ralign 7:0.4974}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 5:1,564}{txt}{col 56}{lalign 13:Adj R-squared}{col 69} = {res}{ralign 7:0.4951}
{txt}{col 56}{lalign 13:Root MSE}{col 69} = {res}{ralign 7:0.3529}

{txt}{ralign 80:(Std. err. adjusted for multiway clustering)}
{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}  reppartyvote{col 16}{c |} Coefficient{col 28}  std. err.{col 40}      t{col 48}   P>|t|{col 56}     [95% con{col 69}f. interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
fordleadership {c |}{col 16}{res}{space 2}-.1295225{col 28}{space 2} .0290558{col 39}{space 1}   -4.46{col 48}{space 3}0.002{col 56}{space 4}-.1952513{col 69}{space 3}-.0637937
{txt}{space 4}ford_ford1 {c |}{col 16}{res}{space 2} .0022278{col 28}{space 2} .0083923{col 39}{space 1}    0.27{col 48}{space 3}0.797{col 56}{space 4}-.0167569{col 69}{space 3} .0212124
{txt}{space 9}_cons {c |}{col 16}{res}{space 2} .4762962{col 28}{space 2} .0096958{col 39}{space 1}   49.12{col 48}{space 3}0.000{col 56}{space 4} .4543628{col 69}{space 3} .4982297
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table2_republicandirection.txt", append 2aster dec(3)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table2_republicandirection.txt""':seeout}

{com}. areg reppartyvote fordleadership ford_ford2, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}    .00738
{txt}Iteration 2:  Maximum absolute difference ={res}  .0001316
{txt}Iteration 3:  Maximum absolute difference ={res} 2.103e-06
{txt}Iteration 4:  Maximum absolute difference ={res} 1.316e-08
{txt}Iteration 5:  Maximum absolute difference ={res} 9.449e-11

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}    .02583
{txt}Iteration 2:  Maximum absolute difference ={res}  .0003896
{txt}Iteration 3:  Maximum absolute difference ={res} 5.587e-06
{txt}Iteration 4:  Maximum absolute difference ={res} 1.820e-08
{txt}Iteration 5:  Maximum absolute difference ={res} 1.509e-10

{txt}{col 1}Linear regression, absorbing indicators{col 56}{lalign 13:Number of obs}{col 69} = {res}{ralign 7:437,693}
{txt}{col 56}{lalign 13:Cluster comb.}{col 69} = {res}{ralign 7:3}
{txt}{col 1}Clusters per comb.:{col 56}{lalign 13:F({res:2}, {res:9})}{col 69} = {res}{ralign 7:11.29}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 5:10}{txt}{col 56}{lalign 13:Prob > F}{col 69} = {res}{ralign 7:0.0035}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 5:643}{txt}{col 56}{lalign 13:R-squared}{col 69} = {res}{ralign 7:0.4974}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 5:1,564}{txt}{col 56}{lalign 13:Adj R-squared}{col 69} = {res}{ralign 7:0.4951}
{txt}{col 56}{lalign 13:Root MSE}{col 69} = {res}{ralign 7:0.3529}

{txt}{ralign 80:(Std. err. adjusted for multiway clustering)}
{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}  reppartyvote{col 16}{c |} Coefficient{col 28}  std. err.{col 40}      t{col 48}   P>|t|{col 56}     [95% con{col 69}f. interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
fordleadership {c |}{col 16}{res}{space 2}-.1279359{col 28}{space 2} .0281605{col 39}{space 1}   -4.54{col 48}{space 3}0.001{col 56}{space 4}-.1916393{col 69}{space 3}-.0642325
{txt}{space 4}ford_ford2 {c |}{col 16}{res}{space 2}-.0011099{col 28}{space 2} .0084292{col 39}{space 1}   -0.13{col 48}{space 3}0.898{col 56}{space 4}-.0201781{col 69}{space 3} .0179583
{txt}{space 9}_cons {c |}{col 16}{res}{space 2} .4762987{col 28}{space 2} .0097015{col 39}{space 1}   49.10{col 48}{space 3}0.000{col 56}{space 4} .4543524{col 69}{space 3} .4982449
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table2_republicandirection.txt", append 2aster dec(3)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table2_republicandirection.txt""':seeout}

{com}. areg reppartyvote fordleadership if congress >= 88 & congress <= 89, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}    .00252
{txt}Iteration 2:  Maximum absolute difference ={res} .00004294
{txt}Iteration 3:  Maximum absolute difference ={res} 6.005e-08
{txt}Iteration 4:  Maximum absolute difference ={res} 1.354e-10

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}    .01221
{txt}Iteration 2:  Maximum absolute difference ={res} .00002347
{txt}Iteration 3:  Maximum absolute difference ={res} 7.028e-08
{txt}Iteration 4:  Maximum absolute difference ={res} 7.454e-11
{txt}{p 0 6 2}note: multiway-cluster variance{ch_endash}covariance {helpb j_cluster_multiway_pd:matrix} is not positive semidefinite.{p_end}

{col 1}Linear regression, absorbing indicators{col 56}{lalign 13:Number of obs}{col 69} = {res}{ralign 7:173,956}
{txt}{col 56}{lalign 13:Cluster comb.}{col 69} = {res}{ralign 7:3}
{txt}{col 1}Clusters per comb.:{col 56}{lalign 13:F({res:1}, {res:3})}{col 69} = {res}{ralign 7:120.80}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 3:4}{txt}{col 56}{lalign 13:Prob > F}{col 69} = {res}{ralign 7:0.0016}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 3:351}{txt}{col 56}{lalign 13:R-squared}{col 69} = {res}{ralign 7:0.5083}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 3:694}{txt}{col 56}{lalign 13:Adj R-squared}{col 69} = {res}{ralign 7:0.5057}
{txt}{col 56}{lalign 13:Root MSE}{col 69} = {res}{ralign 7:0.3468}

{txt}{ralign 80:(Std. err. adjusted for multiway clustering)}
{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}  reppartyvote{col 16}{c |} Coefficient{col 28}  std. err.{col 40}      t{col 48}   P>|t|{col 56}     [95% con{col 69}f. interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
fordleadership {c |}{col 16}{res}{space 2}-.0502092{col 28}{space 2} .0045682{col 39}{space 1}  -10.99{col 48}{space 3}0.002{col 56}{space 4}-.0647472{col 69}{space 3}-.0356712
{txt}{space 9}_cons {c |}{col 16}{res}{space 2} .4286492{col 28}{space 2} .0009627{col 39}{space 1}  445.24{col 48}{space 3}0.000{col 56}{space 4} .4255854{col 69}{space 3} .4317131
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table2_republicandirection.txt", append 2aster dec(3)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table2_republicandirection.txt""':seeout}

{com}. areg reppartyvote fordleadership ford_ford1 if congress >= 88 & congress <= 89, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}    .00252
{txt}Iteration 2:  Maximum absolute difference ={res} .00004294
{txt}Iteration 3:  Maximum absolute difference ={res} 6.005e-08
{txt}Iteration 4:  Maximum absolute difference ={res} 1.354e-10

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}    .01221
{txt}Iteration 2:  Maximum absolute difference ={res} .00002347
{txt}Iteration 3:  Maximum absolute difference ={res} 7.028e-08
{txt}Iteration 4:  Maximum absolute difference ={res} 7.454e-11
{txt}{p 0 6 2}note: multiway-cluster variance{ch_endash}covariance {helpb j_cluster_multiway_pd:matrix} is not positive semidefinite.{p_end}

{col 1}Linear regression, absorbing indicators{col 56}{lalign 13:Number of obs}{col 69} = {res}{ralign 7:173,956}
{txt}{col 56}{lalign 13:Cluster comb.}{col 69} = {res}{ralign 7:3}
{txt}{col 1}Clusters per comb.:{col 56}{lalign 13:F({res:2}, {res:3})}{col 69} = {res}{ralign 7:62.08}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 3:4}{txt}{col 56}{lalign 13:Prob > F}{col 69} = {res}{ralign 7:0.0036}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 3:351}{txt}{col 56}{lalign 13:R-squared}{col 69} = {res}{ralign 7:0.5084}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 3:694}{txt}{col 56}{lalign 13:Adj R-squared}{col 69} = {res}{ralign 7:0.5057}
{txt}{col 56}{lalign 13:Root MSE}{col 69} = {res}{ralign 7:0.3468}

{txt}{ralign 80:(Std. err. adjusted for multiway clustering)}
{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}  reppartyvote{col 16}{c |} Coefficient{col 28}  std. err.{col 40}      t{col 48}   P>|t|{col 56}     [95% con{col 69}f. interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
fordleadership {c |}{col 16}{res}{space 2}-.0429861{col 28}{space 2} .0053497{col 39}{space 1}   -8.04{col 48}{space 3}0.004{col 56}{space 4}-.0600113{col 69}{space 3} -.025961
{txt}{space 4}ford_ford1 {c |}{col 16}{res}{space 2} -.014369{col 28}{space 2} .0064225{col 39}{space 1}   -2.24{col 48}{space 3}0.111{col 56}{space 4}-.0348081{col 69}{space 3} .0060702
{txt}{space 9}_cons {c |}{col 16}{res}{space 2} .4286651{col 28}{space 2} .0009478{col 39}{space 1}  452.27{col 48}{space 3}0.000{col 56}{space 4} .4256488{col 69}{space 3} .4316815
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table2_republicandirection.txt", append 2aster dec(3)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table2_republicandirection.txt""':seeout}

{com}. areg reppartyvote fordleadership ford_ford2 if congress >= 88 & congress <= 89, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}    .00252
{txt}Iteration 2:  Maximum absolute difference ={res} .00004294
{txt}Iteration 3:  Maximum absolute difference ={res} 6.005e-08
{txt}Iteration 4:  Maximum absolute difference ={res} 1.354e-10

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}    .01221
{txt}Iteration 2:  Maximum absolute difference ={res} .00002347
{txt}Iteration 3:  Maximum absolute difference ={res} 7.028e-08
{txt}Iteration 4:  Maximum absolute difference ={res} 7.454e-11
{txt}{p 0 6 2}note: multiway-cluster variance{ch_endash}covariance {helpb j_cluster_multiway_pd:matrix} is not positive semidefinite.{p_end}

{col 1}Linear regression, absorbing indicators{col 56}{lalign 13:Number of obs}{col 69} = {res}{ralign 7:173,956}
{txt}{col 56}{lalign 13:Cluster comb.}{col 69} = {res}{ralign 7:3}
{txt}{col 1}Clusters per comb.:{col 56}{lalign 13:F({res:2}, {res:3})}{col 69} = {res}{ralign 7:60.96}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 3:4}{txt}{col 56}{lalign 13:Prob > F}{col 69} = {res}{ralign 7:0.0037}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 3:351}{txt}{col 56}{lalign 13:R-squared}{col 69} = {res}{ralign 7:0.5084}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 3:694}{txt}{col 56}{lalign 13:Adj R-squared}{col 69} = {res}{ralign 7:0.5057}
{txt}{col 56}{lalign 13:Root MSE}{col 69} = {res}{ralign 7:0.3468}

{txt}{ralign 80:(Std. err. adjusted for multiway clustering)}
{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}  reppartyvote{col 16}{c |} Coefficient{col 28}  std. err.{col 40}      t{col 48}   P>|t|{col 56}     [95% con{col 69}f. interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
fordleadership {c |}{col 16}{res}{space 2}-.0445738{col 28}{space 2} .0056852{col 39}{space 1}   -7.84{col 48}{space 3}0.004{col 56}{space 4}-.0626666{col 69}{space 3} -.026481
{txt}{space 4}ford_ford2 {c |}{col 16}{res}{space 2}-.0099812{col 28}{space 2} .0067192{col 39}{space 1}   -1.49{col 48}{space 3}0.234{col 56}{space 4}-.0313647{col 69}{space 3} .0114023
{txt}{space 9}_cons {c |}{col 16}{res}{space 2} .4286606{col 28}{space 2}  .000947{col 39}{space 1}  452.63{col 48}{space 3}0.000{col 56}{space 4} .4256467{col 69}{space 3} .4316745
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table2_republicandirection.txt", append 2aster dec(3)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table2_republicandirection.txt""':seeout}

{com}. 
. areg withrepublicans fordleadership, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}    .00956
{txt}Iteration 2:  Maximum absolute difference ={res}  .0001736
{txt}Iteration 3:  Maximum absolute difference ={res} 4.999e-07
{txt}Iteration 4:  Maximum absolute difference ={res} 4.887e-09

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}    .02583
{txt}Iteration 2:  Maximum absolute difference ={res}  .0003896
{txt}Iteration 3:  Maximum absolute difference ={res} 5.587e-06
{txt}Iteration 4:  Maximum absolute difference ={res} 1.820e-08
{txt}Iteration 5:  Maximum absolute difference ={res} 1.509e-10

{txt}{col 1}Linear regression, absorbing indicators{col 56}{lalign 13:Number of obs}{col 69} = {res}{ralign 7:437,693}
{txt}{col 56}{lalign 13:Cluster comb.}{col 69} = {res}{ralign 7:3}
{txt}{col 1}Clusters per comb.:{col 56}{lalign 13:F({res:1}, {res:9})}{col 69} = {res}{ralign 7:12.85}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 5:10}{txt}{col 56}{lalign 13:Prob > F}{col 69} = {res}{ralign 7:0.0059}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 5:643}{txt}{col 56}{lalign 13:R-squared}{col 69} = {res}{ralign 7:0.3592}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 5:1,564}{txt}{col 56}{lalign 13:Adj R-squared}{col 69} = {res}{ralign 7:0.3562}
{txt}{col 56}{lalign 13:Root MSE}{col 69} = {res}{ralign 7:0.3791}

{txt}{ralign 80:(Std. err. adjusted for multiway clustering)}
{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}withrepublic~s{col 16}{c |} Coefficient{col 28}  std. err.{col 40}      t{col 48}   P>|t|{col 56}     [95% con{col 69}f. interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
fordleadership {c |}{col 16}{res}{space 2} -.104836{col 28}{space 2} .0292453{col 39}{space 1}   -3.58{col 48}{space 3}0.006{col 56}{space 4}-.1709935{col 69}{space 3}-.0386785
{txt}{space 9}_cons {c |}{col 16}{res}{space 2} .6914289{col 28}{space 2} .0102877{col 39}{space 1}   67.21{col 48}{space 3}0.000{col 56}{space 4} .6681564{col 69}{space 3} .7147014
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table2_withrepublicans.txt", replace 2aster dec(3)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table2_withrepublicans.txt""':seeout}

{com}. areg withrepublicans fordleadership ford_ford1, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}    .00956
{txt}Iteration 2:  Maximum absolute difference ={res}  .0001736
{txt}Iteration 3:  Maximum absolute difference ={res} 4.999e-07
{txt}Iteration 4:  Maximum absolute difference ={res} 4.887e-09

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}    .02583
{txt}Iteration 2:  Maximum absolute difference ={res}  .0003896
{txt}Iteration 3:  Maximum absolute difference ={res} 5.587e-06
{txt}Iteration 4:  Maximum absolute difference ={res} 1.820e-08
{txt}Iteration 5:  Maximum absolute difference ={res} 1.509e-10

{txt}{col 1}Linear regression, absorbing indicators{col 56}{lalign 13:Number of obs}{col 69} = {res}{ralign 7:437,693}
{txt}{col 56}{lalign 13:Cluster comb.}{col 69} = {res}{ralign 7:3}
{txt}{col 1}Clusters per comb.:{col 56}{lalign 13:F({res:2}, {res:9})}{col 69} = {res}{ralign 7:8.39}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 5:10}{txt}{col 56}{lalign 13:Prob > F}{col 69} = {res}{ralign 7:0.0088}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 5:643}{txt}{col 56}{lalign 13:R-squared}{col 69} = {res}{ralign 7:0.3592}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 5:1,564}{txt}{col 56}{lalign 13:Adj R-squared}{col 69} = {res}{ralign 7:0.3562}
{txt}{col 56}{lalign 13:Root MSE}{col 69} = {res}{ralign 7:0.3791}

{txt}{ralign 80:(Std. err. adjusted for multiway clustering)}
{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}withrepublic~s{col 16}{c |} Coefficient{col 28}  std. err.{col 40}      t{col 48}   P>|t|{col 56}     [95% con{col 69}f. interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
fordleadership {c |}{col 16}{res}{space 2}-.1044677{col 28}{space 2} .0322373{col 39}{space 1}   -3.24{col 48}{space 3}0.010{col 56}{space 4}-.1773936{col 69}{space 3}-.0315418
{txt}{space 4}ford_ford1 {c |}{col 16}{res}{space 2}-.0008098{col 28}{space 2} .0122168{col 39}{space 1}   -0.07{col 48}{space 3}0.949{col 56}{space 4}-.0284461{col 69}{space 3} .0268264
{txt}{space 9}_cons {c |}{col 16}{res}{space 2} .6914294{col 28}{space 2} .0102885{col 39}{space 1}   67.20{col 48}{space 3}0.000{col 56}{space 4} .6681552{col 69}{space 3} .7147036
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table2_withrepublicans.txt", append 2aster dec(3)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table2_withrepublicans.txt""':seeout}

{com}. areg withrepublicans fordleadership ford_ford2, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}    .00956
{txt}Iteration 2:  Maximum absolute difference ={res}  .0001736
{txt}Iteration 3:  Maximum absolute difference ={res} 4.999e-07
{txt}Iteration 4:  Maximum absolute difference ={res} 4.887e-09

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}    .02583
{txt}Iteration 2:  Maximum absolute difference ={res}  .0003896
{txt}Iteration 3:  Maximum absolute difference ={res} 5.587e-06
{txt}Iteration 4:  Maximum absolute difference ={res} 1.820e-08
{txt}Iteration 5:  Maximum absolute difference ={res} 1.509e-10

{txt}{col 1}Linear regression, absorbing indicators{col 56}{lalign 13:Number of obs}{col 69} = {res}{ralign 7:437,693}
{txt}{col 56}{lalign 13:Cluster comb.}{col 69} = {res}{ralign 7:3}
{txt}{col 1}Clusters per comb.:{col 56}{lalign 13:F({res:2}, {res:9})}{col 69} = {res}{ralign 7:7.31}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 5:10}{txt}{col 56}{lalign 13:Prob > F}{col 69} = {res}{ralign 7:0.0130}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 5:643}{txt}{col 56}{lalign 13:R-squared}{col 69} = {res}{ralign 7:0.3592}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 5:1,564}{txt}{col 56}{lalign 13:Adj R-squared}{col 69} = {res}{ralign 7:0.3562}
{txt}{col 56}{lalign 13:Root MSE}{col 69} = {res}{ralign 7:0.3791}

{txt}{ralign 80:(Std. err. adjusted for multiway clustering)}
{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}withrepublic~s{col 16}{c |} Coefficient{col 28}  std. err.{col 40}      t{col 48}   P>|t|{col 56}     [95% con{col 69}f. interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
fordleadership {c |}{col 16}{res}{space 2}-.1043606{col 28}{space 2} .0322268{col 39}{space 1}   -3.24{col 48}{space 3}0.010{col 56}{space 4}-.1772628{col 69}{space 3}-.0314584
{txt}{space 4}ford_ford2 {c |}{col 16}{res}{space 2}-.0009201{col 28}{space 2}  .013444{col 39}{space 1}   -0.07{col 48}{space 3}0.947{col 56}{space 4}-.0313325{col 69}{space 3} .0294924
{txt}{space 9}_cons {c |}{col 16}{res}{space 2} .6914298{col 28}{space 2} .0102877{col 39}{space 1}   67.21{col 48}{space 3}0.000{col 56}{space 4} .6681573{col 69}{space 3} .7147022
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table2_withrepublicans.txt", append 2aster dec(3)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table2_withrepublicans.txt""':seeout}

{com}. areg withrepublicans fordleadership if congress >= 88 & congress <= 89, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}   .003195
{txt}Iteration 2:  Maximum absolute difference ={res} .00003381
{txt}Iteration 3:  Maximum absolute difference ={res} 1.968e-07
{txt}Iteration 4:  Maximum absolute difference ={res} 3.395e-10

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}    .01221
{txt}Iteration 2:  Maximum absolute difference ={res} .00002347
{txt}Iteration 3:  Maximum absolute difference ={res} 7.028e-08
{txt}Iteration 4:  Maximum absolute difference ={res} 7.454e-11
{txt}{p 0 6 2}note: multiway-cluster variance{ch_endash}covariance {helpb j_cluster_multiway_pd:matrix} is not positive semidefinite.{p_end}

{col 1}Linear regression, absorbing indicators{col 56}{lalign 13:Number of obs}{col 69} = {res}{ralign 7:173,956}
{txt}{col 56}{lalign 13:Cluster comb.}{col 69} = {res}{ralign 7:3}
{txt}{col 1}Clusters per comb.:{col 56}{lalign 13:F({res:1}, {res:3})}{col 69} = {res}{ralign 7:30.05}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 3:4}{txt}{col 56}{lalign 13:Prob > F}{col 69} = {res}{ralign 7:0.0119}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 3:351}{txt}{col 56}{lalign 13:R-squared}{col 69} = {res}{ralign 7:0.4023}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 3:694}{txt}{col 56}{lalign 13:Adj R-squared}{col 69} = {res}{ralign 7:0.3990}
{txt}{col 56}{lalign 13:Root MSE}{col 69} = {res}{ralign 7:0.3755}

{txt}{ralign 80:(Std. err. adjusted for multiway clustering)}
{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}withrepublic~s{col 16}{c |} Coefficient{col 28}  std. err.{col 40}      t{col 48}   P>|t|{col 56}     [95% con{col 69}f. interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
fordleadership {c |}{col 16}{res}{space 2} -.024933{col 28}{space 2} .0045486{col 39}{space 1}   -5.48{col 48}{space 3}0.012{col 56}{space 4}-.0394088{col 69}{space 3}-.0104573
{txt}{space 9}_cons {c |}{col 16}{res}{space 2} .6289513{col 28}{space 2} .0009421{col 39}{space 1}  667.57{col 48}{space 3}0.000{col 56}{space 4}  .625953{col 69}{space 3} .6319496
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table2_withrepublicans.txt", append 2aster dec(3)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table2_withrepublicans.txt""':seeout}

{com}. areg withrepublicans fordleadership ford_ford1 if congress >= 88 & congress <= 89, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}   .003195
{txt}Iteration 2:  Maximum absolute difference ={res} .00003381
{txt}Iteration 3:  Maximum absolute difference ={res} 1.968e-07
{txt}Iteration 4:  Maximum absolute difference ={res} 3.395e-10

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}    .01221
{txt}Iteration 2:  Maximum absolute difference ={res} .00002347
{txt}Iteration 3:  Maximum absolute difference ={res} 7.028e-08
{txt}Iteration 4:  Maximum absolute difference ={res} 7.454e-11
{txt}{p 0 6 2}note: multiway-cluster variance{ch_endash}covariance {helpb j_cluster_multiway_pd:matrix} is not positive semidefinite.{p_end}

{col 1}Linear regression, absorbing indicators{col 56}{lalign 13:Number of obs}{col 69} = {res}{ralign 7:173,956}
{txt}{col 56}{lalign 13:Cluster comb.}{col 69} = {res}{ralign 7:3}
{txt}{col 1}Clusters per comb.:{col 56}{lalign 13:F({res:2}, {res:3})}{col 69} = {res}{ralign 7:15.34}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 3:4}{txt}{col 56}{lalign 13:Prob > F}{col 69} = {res}{ralign 7:0.0266}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 3:351}{txt}{col 56}{lalign 13:R-squared}{col 69} = {res}{ralign 7:0.4023}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 3:694}{txt}{col 56}{lalign 13:Adj R-squared}{col 69} = {res}{ralign 7:0.3990}
{txt}{col 56}{lalign 13:Root MSE}{col 69} = {res}{ralign 7:0.3755}

{txt}{ralign 80:(Std. err. adjusted for multiway clustering)}
{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}withrepublic~s{col 16}{c |} Coefficient{col 28}  std. err.{col 40}      t{col 48}   P>|t|{col 56}     [95% con{col 69}f. interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
fordleadership {c |}{col 16}{res}{space 2}-.0198832{col 28}{space 2} .0051934{col 39}{space 1}   -3.83{col 48}{space 3}0.031{col 56}{space 4}-.0364108{col 69}{space 3}-.0033556
{txt}{space 4}ford_ford1 {c |}{col 16}{res}{space 2}-.0100457{col 28}{space 2} .0067067{col 39}{space 1}   -1.50{col 48}{space 3}0.231{col 56}{space 4}-.0313893{col 69}{space 3}  .011298
{txt}{space 9}_cons {c |}{col 16}{res}{space 2} .6289624{col 28}{space 2} .0009305{col 39}{space 1}  675.92{col 48}{space 3}0.000{col 56}{space 4} .6260011{col 69}{space 3} .6319238
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table2_withrepublicans.txt", append 2aster dec(3)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table2_withrepublicans.txt""':seeout}

{com}. areg withrepublicans fordleadership ford_ford2 if congress >= 88 & congress <= 89, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}   .003195
{txt}Iteration 2:  Maximum absolute difference ={res} .00003381
{txt}Iteration 3:  Maximum absolute difference ={res} 1.968e-07
{txt}Iteration 4:  Maximum absolute difference ={res} 3.395e-10

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}    .01221
{txt}Iteration 2:  Maximum absolute difference ={res} .00002347
{txt}Iteration 3:  Maximum absolute difference ={res} 7.028e-08
{txt}Iteration 4:  Maximum absolute difference ={res} 7.454e-11
{txt}{p 0 6 2}note: multiway-cluster variance{ch_endash}covariance {helpb j_cluster_multiway_pd:matrix} is not positive semidefinite.{p_end}

{col 1}Linear regression, absorbing indicators{col 56}{lalign 13:Number of obs}{col 69} = {res}{ralign 7:173,956}
{txt}{col 56}{lalign 13:Cluster comb.}{col 69} = {res}{ralign 7:3}
{txt}{col 1}Clusters per comb.:{col 56}{lalign 13:F({res:2}, {res:3})}{col 69} = {res}{ralign 7:15.31}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 3:4}{txt}{col 56}{lalign 13:Prob > F}{col 69} = {res}{ralign 7:0.0267}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 3:351}{txt}{col 56}{lalign 13:R-squared}{col 69} = {res}{ralign 7:0.4023}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 3:694}{txt}{col 56}{lalign 13:Adj R-squared}{col 69} = {res}{ralign 7:0.3990}
{txt}{col 56}{lalign 13:Root MSE}{col 69} = {res}{ralign 7:0.3755}

{txt}{ralign 80:(Std. err. adjusted for multiway clustering)}
{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}withrepublic~s{col 16}{c |} Coefficient{col 28}  std. err.{col 40}      t{col 48}   P>|t|{col 56}     [95% con{col 69}f. interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
fordleadership {c |}{col 16}{res}{space 2}-.0232189{col 28}{space 2} .0053558{col 39}{space 1}   -4.34{col 48}{space 3}0.023{col 56}{space 4}-.0402633{col 69}{space 3}-.0061745
{txt}{space 4}ford_ford2 {c |}{col 16}{res}{space 2} -.003036{col 28}{space 2} .0069923{col 39}{space 1}   -0.43{col 48}{space 3}0.693{col 56}{space 4}-.0252887{col 69}{space 3} .0192167
{txt}{space 9}_cons {c |}{col 16}{res}{space 2} .6289548{col 28}{space 2} .0009311{col 39}{space 1}  675.49{col 48}{space 3}0.000{col 56}{space 4} .6259915{col 69}{space 3}  .631918
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table2_withrepublicans.txt", append 2aster dec(3)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table2_withrepublicans.txt""':seeout}

{com}. 
. areg againstdemocrats fordleadership, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}   .005971
{txt}Iteration 2:  Maximum absolute difference ={res}  .0001658
{txt}Iteration 3:  Maximum absolute difference ={res} 1.067e-06
{txt}Iteration 4:  Maximum absolute difference ={res} 6.042e-09

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}    .02583
{txt}Iteration 2:  Maximum absolute difference ={res}  .0003896
{txt}Iteration 3:  Maximum absolute difference ={res} 5.587e-06
{txt}Iteration 4:  Maximum absolute difference ={res} 1.820e-08
{txt}Iteration 5:  Maximum absolute difference ={res} 1.509e-10

{txt}{col 1}Linear regression, absorbing indicators{col 56}{lalign 13:Number of obs}{col 69} = {res}{ralign 7:437,693}
{txt}{col 56}{lalign 13:Cluster comb.}{col 69} = {res}{ralign 7:3}
{txt}{col 1}Clusters per comb.:{col 56}{lalign 13:F({res:1}, {res:9})}{col 69} = {res}{ralign 7:22.72}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 5:10}{txt}{col 56}{lalign 13:Prob > F}{col 69} = {res}{ralign 7:0.0010}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 5:643}{txt}{col 56}{lalign 13:R-squared}{col 69} = {res}{ralign 7:0.3365}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 5:1,564}{txt}{col 56}{lalign 13:Adj R-squared}{col 69} = {res}{ralign 7:0.3334}
{txt}{col 56}{lalign 13:Root MSE}{col 69} = {res}{ralign 7:0.3641}

{txt}{ralign 80:(Std. err. adjusted for multiway clustering)}
{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}againstdemoc~s{col 16}{c |} Coefficient{col 28}  std. err.{col 40}      t{col 48}   P>|t|{col 56}     [95% con{col 69}f. interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
fordleadership {c |}{col 16}{res}{space 2}-.1503882{col 28}{space 2} .0315503{col 39}{space 1}   -4.77{col 48}{space 3}0.001{col 56}{space 4}  -.22176{col 69}{space 3}-.0790165
{txt}{space 9}_cons {c |}{col 16}{res}{space 2} .3137271{col 28}{space 2} .0112902{col 39}{space 1}   27.79{col 48}{space 3}0.000{col 56}{space 4} .2881868{col 69}{space 3} .3392674
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table2_againstdemocrats.txt", replace 2aster dec(3)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table2_againstdemocrats.txt""':seeout}

{com}. areg againstdemocrats fordleadership ford_ford1, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}   .005971
{txt}Iteration 2:  Maximum absolute difference ={res}  .0001658
{txt}Iteration 3:  Maximum absolute difference ={res} 1.067e-06
{txt}Iteration 4:  Maximum absolute difference ={res} 6.042e-09

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}    .02583
{txt}Iteration 2:  Maximum absolute difference ={res}  .0003896
{txt}Iteration 3:  Maximum absolute difference ={res} 5.587e-06
{txt}Iteration 4:  Maximum absolute difference ={res} 1.820e-08
{txt}Iteration 5:  Maximum absolute difference ={res} 1.509e-10

{txt}{col 1}Linear regression, absorbing indicators{col 56}{lalign 13:Number of obs}{col 69} = {res}{ralign 7:437,693}
{txt}{col 56}{lalign 13:Cluster comb.}{col 69} = {res}{ralign 7:3}
{txt}{col 1}Clusters per comb.:{col 56}{lalign 13:F({res:2}, {res:9})}{col 69} = {res}{ralign 7:11.80}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 5:10}{txt}{col 56}{lalign 13:Prob > F}{col 69} = {res}{ralign 7:0.0030}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 5:643}{txt}{col 56}{lalign 13:R-squared}{col 69} = {res}{ralign 7:0.3365}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 5:1,564}{txt}{col 56}{lalign 13:Adj R-squared}{col 69} = {res}{ralign 7:0.3334}
{txt}{col 56}{lalign 13:Root MSE}{col 69} = {res}{ralign 7:0.3641}

{txt}{ralign 80:(Std. err. adjusted for multiway clustering)}
{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}againstdemoc~s{col 16}{c |} Coefficient{col 28}  std. err.{col 40}      t{col 48}   P>|t|{col 56}     [95% con{col 69}f. interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
fordleadership {c |}{col 16}{res}{space 2}-.1531849{col 28}{space 2} .0327689{col 39}{space 1}   -4.67{col 48}{space 3}0.001{col 56}{space 4}-.2273131{col 69}{space 3}-.0790566
{txt}{space 4}ford_ford1 {c |}{col 16}{res}{space 2} .0061497{col 28}{space 2} .0068362{col 39}{space 1}    0.90{col 48}{space 3}0.392{col 56}{space 4}-.0093149{col 69}{space 3} .0216142
{txt}{space 9}_cons {c |}{col 16}{res}{space 2} .3137234{col 28}{space 2}  .011279{col 39}{space 1}   27.81{col 48}{space 3}0.000{col 56}{space 4} .2882084{col 69}{space 3} .3392384
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table2_againstdemocrats.txt", append 2aster dec(3)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table2_againstdemocrats.txt""':seeout}

{com}. areg againstdemocrats fordleadership ford_ford2, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}   .005971
{txt}Iteration 2:  Maximum absolute difference ={res}  .0001658
{txt}Iteration 3:  Maximum absolute difference ={res} 1.067e-06
{txt}Iteration 4:  Maximum absolute difference ={res} 6.042e-09

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}    .02583
{txt}Iteration 2:  Maximum absolute difference ={res}  .0003896
{txt}Iteration 3:  Maximum absolute difference ={res} 5.587e-06
{txt}Iteration 4:  Maximum absolute difference ={res} 1.820e-08
{txt}Iteration 5:  Maximum absolute difference ={res} 1.509e-10

{txt}{col 1}Linear regression, absorbing indicators{col 56}{lalign 13:Number of obs}{col 69} = {res}{ralign 7:437,693}
{txt}{col 56}{lalign 13:Cluster comb.}{col 69} = {res}{ralign 7:3}
{txt}{col 1}Clusters per comb.:{col 56}{lalign 13:F({res:2}, {res:9})}{col 69} = {res}{ralign 7:11.44}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 5:10}{txt}{col 56}{lalign 13:Prob > F}{col 69} = {res}{ralign 7:0.0034}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 5:643}{txt}{col 56}{lalign 13:R-squared}{col 69} = {res}{ralign 7:0.3365}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 5:1,564}{txt}{col 56}{lalign 13:Adj R-squared}{col 69} = {res}{ralign 7:0.3334}
{txt}{col 56}{lalign 13:Root MSE}{col 69} = {res}{ralign 7:0.3641}

{txt}{ralign 80:(Std. err. adjusted for multiway clustering)}
{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}againstdemoc~s{col 16}{c |} Coefficient{col 28}  std. err.{col 40}      t{col 48}   P>|t|{col 56}     [95% con{col 69}f. interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
fordleadership {c |}{col 16}{res}{space 2}-.1510744{col 28}{space 2}  .031615{col 39}{space 1}   -4.78{col 48}{space 3}0.001{col 56}{space 4}-.2225925{col 69}{space 3}-.0795564
{txt}{space 4}ford_ford2 {c |}{col 16}{res}{space 2}  .001328{col 28}{space 2} .0073251{col 39}{space 1}    0.18{col 48}{space 3}0.860{col 56}{space 4}-.0152425{col 69}{space 3} .0178986
{txt}{space 9}_cons {c |}{col 16}{res}{space 2} .3137258{col 28}{space 2} .0112877{col 39}{space 1}   27.79{col 48}{space 3}0.000{col 56}{space 4} .2881912{col 69}{space 3} .3392604
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table2_againstdemocrats.txt", append 2aster dec(3)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table2_againstdemocrats.txt""':seeout}

{com}. areg againstdemocrats fordleadership if congress >= 88 & congress <= 89, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}   .002375
{txt}Iteration 2:  Maximum absolute difference ={res} 5.387e-06
{txt}Iteration 3:  Maximum absolute difference ={res} 1.065e-07
{txt}Iteration 4:  Maximum absolute difference ={res} 3.307e-10

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}    .01221
{txt}Iteration 2:  Maximum absolute difference ={res} .00002347
{txt}Iteration 3:  Maximum absolute difference ={res} 7.028e-08
{txt}Iteration 4:  Maximum absolute difference ={res} 7.454e-11
{txt}{p 0 6 2}note: multiway-cluster variance{ch_endash}covariance {helpb j_cluster_multiway_pd:matrix} is not positive semidefinite.{p_end}

{col 1}Linear regression, absorbing indicators{col 56}{lalign 13:Number of obs}{col 69} = {res}{ralign 7:173,956}
{txt}{col 56}{lalign 13:Cluster comb.}{col 69} = {res}{ralign 7:3}
{txt}{col 1}Clusters per comb.:{col 56}{lalign 13:F({res:1}, {res:3})}{col 69} = {res}{ralign 7:235.78}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 3:4}{txt}{col 56}{lalign 13:Prob > F}{col 69} = {res}{ralign 7:0.0006}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 3:351}{txt}{col 56}{lalign 13:R-squared}{col 69} = {res}{ralign 7:0.3852}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 3:694}{txt}{col 56}{lalign 13:Adj R-squared}{col 69} = {res}{ralign 7:0.3819}
{txt}{col 56}{lalign 13:Root MSE}{col 69} = {res}{ralign 7:0.3572}

{txt}{ralign 80:(Std. err. adjusted for multiway clustering)}
{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}againstdemoc~s{col 16}{c |} Coefficient{col 28}  std. err.{col 40}      t{col 48}   P>|t|{col 56}     [95% con{col 69}f. interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
fordleadership {c |}{col 16}{res}{space 2}-.0638151{col 28}{space 2} .0041559{col 39}{space 1}  -15.36{col 48}{space 3}0.001{col 56}{space 4}-.0770411{col 69}{space 3}-.0505891
{txt}{space 9}_cons {c |}{col 16}{res}{space 2} .3045408{col 28}{space 2} .0008698{col 39}{space 1}  350.14{col 48}{space 3}0.000{col 56}{space 4} .3017728{col 69}{space 3} .3073088
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table2_againstdemocrats.txt", append 2aster dec(3)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table2_againstdemocrats.txt""':seeout}

{com}. areg againstdemocrats fordleadership ford_ford1 if congress >= 88 & congress <= 89, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}   .002375
{txt}Iteration 2:  Maximum absolute difference ={res} 5.387e-06
{txt}Iteration 3:  Maximum absolute difference ={res} 1.065e-07
{txt}Iteration 4:  Maximum absolute difference ={res} 3.307e-10

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}    .01221
{txt}Iteration 2:  Maximum absolute difference ={res} .00002347
{txt}Iteration 3:  Maximum absolute difference ={res} 7.028e-08
{txt}Iteration 4:  Maximum absolute difference ={res} 7.454e-11
{txt}{p 0 6 2}note: multiway-cluster variance{ch_endash}covariance {helpb j_cluster_multiway_pd:matrix} is not positive semidefinite.{p_end}

{col 1}Linear regression, absorbing indicators{col 56}{lalign 13:Number of obs}{col 69} = {res}{ralign 7:173,956}
{txt}{col 56}{lalign 13:Cluster comb.}{col 69} = {res}{ralign 7:3}
{txt}{col 1}Clusters per comb.:{col 56}{lalign 13:F({res:2}, {res:3})}{col 69} = {res}{ralign 7:120.55}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 3:4}{txt}{col 56}{lalign 13:Prob > F}{col 69} = {res}{ralign 7:0.0014}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 3:351}{txt}{col 56}{lalign 13:R-squared}{col 69} = {res}{ralign 7:0.3853}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 3:694}{txt}{col 56}{lalign 13:Adj R-squared}{col 69} = {res}{ralign 7:0.3819}
{txt}{col 56}{lalign 13:Root MSE}{col 69} = {res}{ralign 7:0.3572}

{txt}{ralign 80:(Std. err. adjusted for multiway clustering)}
{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}againstdemoc~s{col 16}{c |} Coefficient{col 28}  std. err.{col 40}      t{col 48}   P>|t|{col 56}     [95% con{col 69}f. interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
fordleadership {c |}{col 16}{res}{space 2} -.058034{col 28}{space 2} .0050847{col 39}{space 1}  -11.41{col 48}{space 3}0.001{col 56}{space 4}-.0742158{col 69}{space 3}-.0418522
{txt}{space 4}ford_ford1 {c |}{col 16}{res}{space 2}-.0115004{col 28}{space 2} .0059966{col 39}{space 1}   -1.92{col 48}{space 3}0.151{col 56}{space 4}-.0305843{col 69}{space 3} .0075835
{txt}{space 9}_cons {c |}{col 16}{res}{space 2} .3045535{col 28}{space 2}  .000856{col 39}{space 1}  355.79{col 48}{space 3}0.000{col 56}{space 4} .3018294{col 69}{space 3} .3072777
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table2_againstdemocrats.txt", append 2aster dec(3)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table2_againstdemocrats.txt""':seeout}

{com}. areg againstdemocrats fordleadership ford_ford2 if congress >= 88 & congress <= 89, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}   .002375
{txt}Iteration 2:  Maximum absolute difference ={res} 5.387e-06
{txt}Iteration 3:  Maximum absolute difference ={res} 1.065e-07
{txt}Iteration 4:  Maximum absolute difference ={res} 3.307e-10

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}    .01221
{txt}Iteration 2:  Maximum absolute difference ={res} .00002347
{txt}Iteration 3:  Maximum absolute difference ={res} 7.028e-08
{txt}Iteration 4:  Maximum absolute difference ={res} 7.454e-11
{txt}{p 0 6 2}note: multiway-cluster variance{ch_endash}covariance {helpb j_cluster_multiway_pd:matrix} is not positive semidefinite.{p_end}

{col 1}Linear regression, absorbing indicators{col 56}{lalign 13:Number of obs}{col 69} = {res}{ralign 7:173,956}
{txt}{col 56}{lalign 13:Cluster comb.}{col 69} = {res}{ralign 7:3}
{txt}{col 1}Clusters per comb.:{col 56}{lalign 13:F({res:2}, {res:3})}{col 69} = {res}{ralign 7:118.64}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 3:4}{txt}{col 56}{lalign 13:Prob > F}{col 69} = {res}{ralign 7:0.0014}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 3:351}{txt}{col 56}{lalign 13:R-squared}{col 69} = {res}{ralign 7:0.3852}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 3:694}{txt}{col 56}{lalign 13:Adj R-squared}{col 69} = {res}{ralign 7:0.3819}
{txt}{col 56}{lalign 13:Root MSE}{col 69} = {res}{ralign 7:0.3572}

{txt}{ralign 80:(Std. err. adjusted for multiway clustering)}
{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}againstdemoc~s{col 16}{c |} Coefficient{col 28}  std. err.{col 40}      t{col 48}   P>|t|{col 56}     [95% con{col 69}f. interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
fordleadership {c |}{col 16}{res}{space 2}-.0594329{col 28}{space 2} .0053503{col 39}{space 1}  -11.11{col 48}{space 3}0.002{col 56}{space 4}-.0764598{col 69}{space 3} -.042406
{txt}{space 4}ford_ford2 {c |}{col 16}{res}{space 2}-.0077616{col 28}{space 2} .0062827{col 39}{space 1}   -1.24{col 48}{space 3}0.305{col 56}{space 4}-.0277561{col 69}{space 3} .0122329
{txt}{space 9}_cons {c |}{col 16}{res}{space 2} .3045496{col 28}{space 2} .0008554{col 39}{space 1}  356.04{col 48}{space 3}0.000{col 56}{space 4} .3018274{col 69}{space 3} .3072719
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "Table2_againstdemocrats.txt", append 2aster dec(3)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table2_againstdemocrats.txt""':seeout}

{com}. 
. 
. *Table 3
. clear
{txt}
{com}. use "CleanedRollCallData.dta"
{txt}
{com}. keep if house == 0
{txt}(12,461,813 observations deleted)

{com}. keep if congress == 91
{txt}(2,064,836 observations deleted)

{com}. areg conservative noleader scott, a(member_party_chamber bill) vce(cluster member_party_chamber bill)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}   .000867
{txt}Iteration 2:  Maximum absolute difference ={res} 3.068e-06
{txt}Iteration 3:  Maximum absolute difference ={res} 2.069e-08
{txt}Iteration 4:  Maximum absolute difference ={res} 5.622e-11

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}   .002229
{txt}Iteration 2:  Maximum absolute difference ={res} .00001172
{txt}Iteration 3:  Maximum absolute difference ={res} 4.496e-08
{txt}Iteration 4:  Maximum absolute difference ={res} 1.876e-10
{txt}{p 0 6 2}note: multiway-cluster variance{ch_endash}covariance {helpb j_cluster_multiway_pd:matrix} is not positive semidefinite.{p_end}

{col 1}Linear regression, absorbing indicators{col 57}{lalign 13:Number of obs}{col 70} = {res}{ralign 6:50,709}
{txt}{col 57}{lalign 13:Cluster comb.}{col 70} = {res}{ralign 6:3}
{txt}{col 1}Clusters per comb.:{col 57}{lalign 13:F({res:2}, {res:98})}{col 70} = {res}{ralign 6:1.73}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 6:99}{txt}{col 57}{lalign 13:Prob > F}{col 70} = {res}{ralign 6:0.1824}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 6:17,132}{txt}{col 57}{lalign 13:R-squared}{col 70} = {res}{ralign 6:0.4428}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 6:50,709}{txt}{col 57}{lalign 13:Adj R-squared}{col 70} = {res}{ralign 6:0.4352}
{txt}{col 57}{lalign 13:Root MSE}{col 70} = {res}{ralign 6:0.3751}

{txt}{ralign 78:(Std. err. adjusted for multiway clustering)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}conservative{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}noleader {c |}{col 14}{res}{space 2}-.1014597{col 26}{space 2} .0620013{col 37}{space 1}   -1.64{col 46}{space 3}0.105{col 54}{space 4}-.2244993{col 67}{space 3} .0215798
{txt}{space 7}scott {c |}{col 14}{res}{space 2}-.0095539{col 26}{space 2} .0391465{col 37}{space 1}   -0.24{col 46}{space 3}0.808{col 54}{space 4}-.0872389{col 67}{space 3}  .068131
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}  .475315{col 26}{space 2} .0153499{col 37}{space 1}   30.97{col 46}{space 3}0.000{col 54}{space 4} .4448537{col 67}{space 3} .5057763
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:bill}.{p_end}

{com}. outreg2 using "Table3.txt", replace 2aster dec(3)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table3.txt""':seeout}

{com}. areg reppartyvote noleader scott, a(member_party_chamber bill) vce(cluster member_party_chamber bill)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}  .0007848
{txt}Iteration 2:  Maximum absolute difference ={res} 6.341e-06
{txt}Iteration 3:  Maximum absolute difference ={res} 1.724e-08
{txt}Iteration 4:  Maximum absolute difference ={res} 5.519e-11

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}   .002229
{txt}Iteration 2:  Maximum absolute difference ={res} .00001172
{txt}Iteration 3:  Maximum absolute difference ={res} 4.496e-08
{txt}Iteration 4:  Maximum absolute difference ={res} 1.876e-10
{txt}{p 0 6 2}note: multiway-cluster variance{ch_endash}covariance {helpb j_cluster_multiway_pd:matrix} is not positive semidefinite.{p_end}

{col 1}Linear regression, absorbing indicators{col 57}{lalign 13:Number of obs}{col 70} = {res}{ralign 6:50,709}
{txt}{col 57}{lalign 13:Cluster comb.}{col 70} = {res}{ralign 6:3}
{txt}{col 1}Clusters per comb.:{col 57}{lalign 13:F({res:2}, {res:98})}{col 70} = {res}{ralign 6:4.05}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 6:99}{txt}{col 57}{lalign 13:Prob > F}{col 70} = {res}{ralign 6:0.0203}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 6:17,132}{txt}{col 57}{lalign 13:R-squared}{col 70} = {res}{ralign 6:0.3871}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 6:50,709}{txt}{col 57}{lalign 13:Adj R-squared}{col 70} = {res}{ralign 6:0.3787}
{txt}{col 57}{lalign 13:Root MSE}{col 70} = {res}{ralign 6:0.3941}

{txt}{ralign 78:(Std. err. adjusted for multiway clustering)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}reppartyvote{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}noleader {c |}{col 14}{res}{space 2}-.1095389{col 26}{space 2} .0484312{col 37}{space 1}   -2.26{col 46}{space 3}0.026{col 54}{space 4} -.205649{col 67}{space 3}-.0134288
{txt}{space 7}scott {c |}{col 14}{res}{space 2}-.0088234{col 26}{space 2} .0353085{col 37}{space 1}   -0.25{col 46}{space 3}0.803{col 54}{space 4} -.078892{col 67}{space 3} .0612452
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .4965856{col 26}{space 2} .0138361{col 37}{space 1}   35.89{col 46}{space 3}0.000{col 54}{space 4} .4691283{col 67}{space 3} .5240429
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:bill}.{p_end}

{com}. outreg2 using "Table3.txt", append 2aster dec(3)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table3.txt""':seeout}

{com}. areg withrepublicans noleader scott, a(member_party_chamber bill) vce(cluster member_party_chamber bill)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}  .0008387
{txt}Iteration 2:  Maximum absolute difference ={res} 4.409e-06
{txt}Iteration 3:  Maximum absolute difference ={res} 1.890e-08
{txt}Iteration 4:  Maximum absolute difference ={res} 8.795e-11

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}   .002229
{txt}Iteration 2:  Maximum absolute difference ={res} .00001172
{txt}Iteration 3:  Maximum absolute difference ={res} 4.496e-08
{txt}Iteration 4:  Maximum absolute difference ={res} 1.876e-10
{txt}{p 0 6 2}note: multiway-cluster variance{ch_endash}covariance {helpb j_cluster_multiway_pd:matrix} is not positive semidefinite.{p_end}

{col 1}Linear regression, absorbing indicators{col 57}{lalign 13:Number of obs}{col 70} = {res}{ralign 6:50,709}
{txt}{col 57}{lalign 13:Cluster comb.}{col 70} = {res}{ralign 6:3}
{txt}{col 1}Clusters per comb.:{col 57}{lalign 13:F({res:2}, {res:98})}{col 70} = {res}{ralign 6:1.90}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 6:99}{txt}{col 57}{lalign 13:Prob > F}{col 70} = {res}{ralign 6:0.1551}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 6:17,132}{txt}{col 57}{lalign 13:R-squared}{col 70} = {res}{ralign 6:0.2448}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 6:50,709}{txt}{col 57}{lalign 13:Adj R-squared}{col 70} = {res}{ralign 6:0.2344}
{txt}{col 57}{lalign 13:Root MSE}{col 70} = {res}{ralign 6:0.4168}

{txt}{ralign 78:(Std. err. adjusted for multiway clustering)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}withrepubl~s{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}noleader {c |}{col 14}{res}{space 2} -.145181{col 26}{space 2} .0757749{col 37}{space 1}   -1.92{col 46}{space 3}0.058{col 54}{space 4}-.2955538{col 67}{space 3} .0051919
{txt}{space 7}scott {c |}{col 14}{res}{space 2}-.0279506{col 26}{space 2}  .042967{col 37}{space 1}   -0.65{col 46}{space 3}0.517{col 54}{space 4}-.1132173{col 67}{space 3} .0573161
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .6636465{col 26}{space 2} .0168401{col 37}{space 1}   39.41{col 46}{space 3}0.000{col 54}{space 4} .6302279{col 67}{space 3} .6970651
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:bill}.{p_end}

{com}. outreg2 using "Table3.txt", append 2aster dec(3)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table3.txt""':seeout}

{com}. areg againstdemocrats noleader scott, a(member_party_chamber bill) vce(cluster member_party_chamber bill)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}   .001331
{txt}Iteration 2:  Maximum absolute difference ={res} 6.424e-06
{txt}Iteration 3:  Maximum absolute difference ={res} 2.885e-08
{txt}Iteration 4:  Maximum absolute difference ={res} 1.059e-10

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}   .002229
{txt}Iteration 2:  Maximum absolute difference ={res} .00001172
{txt}Iteration 3:  Maximum absolute difference ={res} 4.496e-08
{txt}Iteration 4:  Maximum absolute difference ={res} 1.876e-10
{txt}{p 0 6 2}note: multiway-cluster variance{ch_endash}covariance {helpb j_cluster_multiway_pd:matrix} is not positive semidefinite.{p_end}

{col 1}Linear regression, absorbing indicators{col 57}{lalign 13:Number of obs}{col 70} = {res}{ralign 6:50,709}
{txt}{col 57}{lalign 13:Cluster comb.}{col 70} = {res}{ralign 6:3}
{txt}{col 1}Clusters per comb.:{col 57}{lalign 13:F({res:2}, {res:98})}{col 70} = {res}{ralign 6:3.25}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 6:99}{txt}{col 57}{lalign 13:Prob > F}{col 70} = {res}{ralign 6:0.0429}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 6:17,132}{txt}{col 57}{lalign 13:R-squared}{col 70} = {res}{ralign 6:0.2315}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 6:50,709}{txt}{col 57}{lalign 13:Adj R-squared}{col 70} = {res}{ralign 6:0.2209}
{txt}{col 57}{lalign 13:Root MSE}{col 70} = {res}{ralign 6:0.4139}

{txt}{ralign 78:(Std. err. adjusted for multiway clustering)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}againstdem~s{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}noleader {c |}{col 14}{res}{space 2}-.2134313{col 26}{space 2} .0878393{col 37}{space 1}   -2.43{col 46}{space 3}0.017{col 54}{space 4}-.3877456{col 67}{space 3} -.039117
{txt}{space 7}scott {c |}{col 14}{res}{space 2}-.0261142{col 26}{space 2} .0441248{col 37}{space 1}   -0.59{col 46}{space 3}0.555{col 54}{space 4}-.1136784{col 67}{space 3} .0614499
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .3379385{col 26}{space 2} .0173416{col 37}{space 1}   19.49{col 46}{space 3}0.000{col 54}{space 4} .3035247{col 67}{space 3} .3723523
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:bill}.{p_end}

{com}. outreg2 using "Table3.txt", append 2aster dec(3)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "Table3.txt""':seeout}

{com}. 
. 
. *Appendix Figure A1
. clear
{txt}
{com}. postutil clear
{txt}
{com}. use "CVP_1_117.dta"
{txt}
{com}. keep chamber congress icpsr party cvp_gls_adjusted
{txt}
{com}. g house = chamber == "House"
{txt}
{com}. keep if party == 100 | party == 200
{txt}(7,087 observations deleted)

{com}. g dem = party == 100
{txt}
{com}. drop party chamber
{txt}
{com}. rename cvp cvp
{res}{txt}
{com}. merge m:1 icpsr dem house using "HouseSenateLeaders.dta"
{res}{txt}{p 0 7 2}
(variable
{bf:icpsr} was {bf:long}, now {bf:double} to accommodate using data's values)
{p_end}

{col 5}Result{col 33}Number of obs
{col 5}{hline 41}
{col 5}Not matched{col 30}{res}          41,922
{txt}{col 9}from master{col 30}{res}          41,922{txt}  (_merge==1)
{col 9}from using{col 30}{res}               0{txt}  (_merge==2)

{col 5}Matched{col 30}{res}             495{txt}  (_merge==3)
{col 5}{hline 41}

{com}. keep if _merge == 3
{txt}(41,922 observations deleted)

{com}. drop _merge
{txt}
{com}. drop if congress >= mincong
{txt}(187 observations deleted)

{com}. preserve
{txt}
{com}. collapse (mean) cvp house dem, by(icpsr)
{res}{txt}
{com}. merge 1:1 icpsr house dem using "HouseSenateLeaders.dta"
{res}
{txt}{col 5}Result{col 33}Number of obs
{col 5}{hline 41}
{col 5}Not matched{col 30}{res}               0
{txt}{col 5}Matched{col 30}{res}              39{txt}  (_merge==3)
{col 5}{hline 41}

{com}. drop _merge
{txt}
{com}. rename mincong cong0
{res}{txt}
{com}. forvalues i = 1/15 {c -(}
{txt}  2{com}. g cong`i' = cong0 + `i' if cong0 + `i' <= maxcong 
{txt}  3{com}. {c )-}
{txt}(3 missing values generated)
(9 missing values generated)
(17 missing values generated)
(25 missing values generated)
(30 missing values generated)
(33 missing values generated)
(34 missing values generated)
(36 missing values generated)
(36 missing values generated)
(38 missing values generated)
(39 missing values generated)
(39 missing values generated)
(39 missing values generated)
(39 missing values generated)
(39 missing values generated)

{com}. drop maxcong
{txt}
{com}. reshape long cong, i(icpsr) j(num)
{res}{txt}(j = 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15)

Data{col 36}Wide{col 43}->{col 48}Long
{hline 77}
Number of observations     {res}          39   {txt}->   {res}624         
{txt}Number of variables        {res}          20   {txt}->   {res}6           
{txt}j variable (16 values)                    ->   {res}num
{txt}xij variables:
                 {res}cong0 cong1 ... cong15   {txt}->   {res}cong
{txt}{hline 77}

{com}. drop if cong == .
{txt}(456 observations deleted)

{com}. drop num
{txt}
{com}. rename icpsr leader_icpsr
{res}{txt}
{com}. sort house dem cong 
{txt}
{com}. rename cvp leader_cvp
{res}{txt}
{com}. rename cong congress
{res}{txt}
{com}. save "Leader_CVP_ICPSR.dta", replace
{txt}{p 0 4 2}
(file {bf}
Leader_CVP_ICPSR.dta{rm}
not found)
{p_end}
{p 0 4 2}
file {bf}
Leader_CVP_ICPSR.dta{rm}
saved
{p_end}

{com}. keep if congress >= 77 & congress <= 116
{txt}(8 observations deleted)

{com}. keep leader_*
{txt}
{com}. collapse leader_cvp, by(leader_icpsr)
{res}{txt}
{com}. save "Leader_CVP_temp.dta", replace
{txt}{p 0 4 2}
(file {bf}
Leader_CVP_temp.dta{rm}
not found)
{p_end}
{p 0 4 2}
file {bf}
Leader_CVP_temp.dta{rm}
saved
{p_end}

{com}. keep if leader_icpsr == 437 | leader_icpsr == 6367 | leader_icpsr == 7753 | leader_icpsr == 6033 
{txt}(35 observations deleted)

{com}. save "firstleaders.dta", replace
{txt}{p 0 4 2}
(file {bf}
firstleaders.dta{rm}
not found)
{p_end}
{p 0 4 2}
file {bf}
firstleaders.dta{rm}
saved
{p_end}

{com}. restore
{txt}
{com}. drop mincong maxcong
{txt}
{com}. merge m:1 congress house dem using "Leader_CVP_ICPSR.dta"
{res}
{txt}{col 5}Result{col 33}Number of obs
{col 5}{hline 41}
{col 5}Not matched{col 30}{res}              73
{txt}{col 9}from master{col 30}{res}              49{txt}  (_merge==1)
{col 9}from using{col 30}{res}              24{txt}  (_merge==2)

{col 5}Matched{col 30}{res}             259{txt}  (_merge==3)
{col 5}{hline 41}

{com}. keep if _merge == 3
{txt}(73 observations deleted)

{com}. egen party_chamber = group(dem house)
{txt}
{com}. g temp = leader_cvp if congress == 77
{txt}(254 missing values generated)

{com}. egen firstleader_cvp = mean(temp), by(party_chamber)
{txt}
{com}. drop temp party_chamber
{txt}
{com}. drop _merge leader_cvp
{txt}
{com}. save "futureleaders.dta", replace
{txt}{p 0 4 2}
(file {bf}
futureleaders.dta{rm}
not found)
{p_end}
{p 0 4 2}
file {bf}
futureleaders.dta{rm}
saved
{p_end}

{com}. clear
{txt}
{com}. use "CleanedRollCallData.dta"
{txt}
{com}. keep if congress >= 77 & congress <= 116
{txt}(587,769 observations deleted)

{com}. drop majority bioname yea reppartyvote withrepublicans againstdemocrats cvp moderate leader_next leader_prev leader_cvp
{txt}
{com}. merge m:1 house dem congress using "Leader_CVP_ICPSR.dta"
{res}
{txt}{col 5}Result{col 33}Number of obs
{col 5}{hline 41}
{col 5}Not matched{col 30}{res}               8
{txt}{col 9}from master{col 30}{res}               0{txt}  (_merge==1)
{col 9}from using{col 30}{res}               8{txt}  (_merge==2)

{col 5}Matched{col 30}{res}      13,989,589{txt}  (_merge==3)
{col 5}{hline 41}

{com}. drop if noleader == 1
{txt}(361 observations deleted)

{com}. sum leader_icpsr if dem == 0 & house == 0 & congress == 90

{txt}    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
leader_icpsr {c |}{res}     17,879        2609           0       2609       2609
{txt}
{com}. replace leader_icpsr = r(mean) if dem == 0 & house == 0 & congress == 91 & scott + noleader == 0
{txt}(2,498 real changes made)

{com}. drop _merge noleader scott leader_cvp
{txt}
{com}. save "CleanedDataForIterative.dta", replace
{txt}{p 0 4 2}
(file {bf}
CleanedDataForIterative.dta{rm}
not found)
{p_end}
{p 0 4 2}
file {bf}
CleanedDataForIterative.dta{rm}
saved
{p_end}

{com}. 
. clear
{txt}
{com}. postutil clear
{txt}
{com}. postfile Results coef sterr pval iteration using "Results.dta", replace
{txt}{p 0 4 2}
(file {bf}
Results.dta{rm}
not found)
{p_end}

{com}. scalar leadereffect = 0
{txt}
{com}. forvalues i = 1/16 {c -(}
{txt}  2{com}. quietly {c -(}
{txt}  3{com}. clear
{txt}  4{com}. use "futureleaders.dta"
{txt}  5{com}. merge m:1 leader_icpsr using "Leader_CVP_temp.dta"
{txt}  6{com}. keep if _merge == 3
{txt}  7{com}. g cvp_corrected = cvp - (leader_cvp - firstleader_cvp)*leadereffect
{txt}  8{com}. collapse cvp_corrected, by(icpsr)
{txt}  9{com}. rename cvp_corrected leader_cvp
{txt} 10{com}. rename icpsr leader_icpsr
{txt} 11{com}. append using "firstleaders.dta"
{txt} 12{com}. save "Leader_CVP_temp.dta", replace
{txt} 13{com}. clear
{txt} 14{com}. use "CleanedDataForIterative.dta"
{txt} 15{com}. merge m:1 leader_icpsr using "Leader_CVP_temp"
{txt} 16{com}. drop _merge
{txt} 17{com}. areg conservative leader_cvp, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{txt} 18{com}. scalar leadereffect = _b[leader_cvp]
{txt} 19{com}. post Results (_b[leader_cvp]) (_se[leader_cvp]) (2*ttail(e(df_r),abs(_b[leader_cvp]/_se[leader_cvp]))) (`i')
{txt} 20{com}. {c )-}
{txt} 21{com}. disp `i' " $S_TIME " leadereffect
{txt} 22{com}. {c )-}
1 21:59:11 .40624374
2 21:59:29 .33064033
3 21:59:47 .34246153
4 22:00:04 .34050556
5 22:00:21 .33990928
6 22:00:39 .34031138
7 22:00:56 .3402014
8 22:01:13 .34022415
9 22:01:30 .34022097
10 22:01:48 .34022056
11 22:02:06 .34022097
12 22:02:24 .34022076
13 22:02:42 .3402208
14 22:03:00 .34022079
15 22:03:18 .34022079
16 22:03:34 .34022079
{txt}
{com}. postclose Results
{txt}
{com}. clear
{txt}
{com}. use "Results.dta"
{txt}
{com}. g upper = coef + sterr*1.96
{txt}
{com}. g lower = coef - sterr*1.96
{txt}
{com}. graph twoway line upper lower coef iteration, yline(0)
{res}{txt}
{com}. gr_edit .plotregion1._xylines[1].style.editstyle linestyle(color(gs8) width(medthin)) editcopy
{res}{txt}
{com}. gr_edit .legend.draw_view.setstyle, style(no)
{res}{txt}
{com}. gr_edit .xaxis1.title.text = {c -(}{c )-}
{res}{txt}
{com}. gr_edit .xaxis1.title.text.Arrpush Iteration
{res}{txt}
{com}. gr_edit .yaxis1.title.text = {c -(}{c )-}
{res}{txt}
{com}. gr_edit .yaxis1.title.text.Arrpush Estimated Leader Effect
{res}{txt}
{com}. gr_edit .xaxis1.reset_rule 1 16 3, tickset(major) ruletype(range) 
{res}{txt}
{com}. gr_edit .yaxis1.reset_rule 0 .6 .2, tickset(major) ruletype(range) 
{res}{txt}
{com}. gr_edit .yaxis1.style.editstyle majorstyle(gridstyle(linestyle(color(white)))) editcopy
{res}{txt}
{com}. gr_edit .xaxis1.style.editstyle majorstyle(gridstyle(linestyle(color(white)))) editcopy
{res}{txt}
{com}. gr_edit .style.editstyle margin(vsmall) boxstyle(shadestyle(color(white)) linestyle(color(white))) editcopy
{res}{txt}
{com}. gr_edit .plotregion1.plot1.style.editstyle line(color(black) width(medthin) pattern(dash)) editcopy
{res}{txt}
{com}. gr_edit .plotregion1.plot2.style.editstyle line(color(black) width(medthin) pattern(dash)) editcopy
{res}{txt}
{com}. gr_edit .plotregion1.plot3.style.editstyle line(color(black) width(thick)) editcopy
{res}{txt}
{com}. graph export "Iterative.png", replace as(png)
{txt}{p 0 4 2}
(file {bf}
Iterative.png{rm}
not found)
{p_end}
{p 0 4 2}
file {bf}
Iterative.png{rm}
saved as
PNG
format
{p_end}

{com}. 
. 
. *Appendix Table 1
. clear
{txt}
{com}. use "SenateAllLeaders.dta"
{txt}
{com}. g whip0 = whip_start
{txt}(12 missing values generated)

{com}. forvalues i = 1/11 {c -(}
{txt}  2{com}. g whip`i' = whip0 + `i' if whip0 + `i' <= whip_end 
{txt}  3{com}. {c )-}
{txt}(19 missing values generated)
(24 missing values generated)
(32 missing values generated)
(36 missing values generated)
(38 missing values generated)
(38 missing values generated)
(39 missing values generated)
(39 missing values generated)
(39 missing values generated)
(39 missing values generated)
(40 missing values generated)

{com}. g leader0 = leader_start
{txt}(19 missing values generated)

{com}. forvalues i = 1/11 {c -(}
{txt}  2{com}. g leader`i' = leader0 + `i' if leader0 + `i' <= leader_end 
{txt}  3{com}. {c )-}
{txt}(21 missing values generated)
(24 missing values generated)
(28 missing values generated)
(31 missing values generated)
(33 missing values generated)
(38 missing values generated)
(38 missing values generated)
(40 missing values generated)
(40 missing values generated)
(40 missing values generated)
(40 missing values generated)

{com}. drop whip_* leader_*
{txt}
{com}. reshape long whip leader, i(icpsr) j(num)
{res}{txt}(j = 0 1 2 3 4 5 6 7 8 9 10 11)

Data{col 36}Wide{col 43}->{col 48}Long
{hline 77}
Number of observations     {res}          40   {txt}->   {res}480         
{txt}Number of variables        {res}          27   {txt}->   {res}6           
{txt}j variable (12 values)                    ->   {res}num
{txt}xij variables:
                 {res}whip0 whip1 ... whip11   {txt}->   {res}whip
           leader0 leader1 ... leader11   {txt}->   {res}leader
{txt}{hline 77}

{com}. drop if whip == . & leader == .
{txt}(323 observations deleted)

{com}. drop num
{txt}
{com}. preserve
{txt}
{com}. drop leader
{txt}
{com}. drop if whip == .
{txt}(72 observations deleted)

{com}. rename whip congress
{res}{txt}
{com}. g whip = 1
{txt}
{com}. save "whip.dta", replace
{txt}{p 0 4 2}
(file {bf}
whip.dta{rm}
not found)
{p_end}
{p 0 4 2}
file {bf}
whip.dta{rm}
saved
{p_end}

{com}. restore
{txt}
{com}. drop whip
{txt}
{com}. drop if leader == .
{txt}(69 observations deleted)

{com}. rename leader congress
{res}{txt}
{com}. g leader = 1
{txt}
{com}. append using "whip.dta"
{txt}
{com}. replace leader = 0 if leader == .
{txt}(85 real changes made)

{com}. replace whip = 0 if whip == .
{txt}(88 real changes made)

{com}. save "SenateAllLeadersCleaned.dta", replace
{txt}{p 0 4 2}
(file {bf}
SenateAllLeadersCleaned.dta{rm}
not found)
{p_end}
{p 0 4 2}
file {bf}
SenateAllLeadersCleaned.dta{rm}
saved
{p_end}

{com}. egen firstcongasleader = min(congress), by(icpsr)
{txt}
{com}. keep icpsr name firstcong
{txt}
{com}. sort icpsr
{txt}
{com}. drop if icpsr == icpsr[_n-1]
{txt}(133 observations deleted)

{com}. save "SenateAllLeadersFirst.dta", replace
{txt}{p 0 4 2}
(file {bf}
SenateAllLeadersFirst.dta{rm}
not found)
{p_end}
{p 0 4 2}
file {bf}
SenateAllLeadersFirst.dta{rm}
saved
{p_end}

{com}. clear
{txt}
{com}. use "CVP_1_117.dta"
{txt}
{com}. rename name name2
{res}{txt}
{com}. keep chamber congress icpsr party cvp_gls_adjusted name2
{txt}
{com}. keep if chamber == "Senate"
{txt}(39,801 observations deleted)

{com}. keep if party == 100 | party == 200
{txt}(1,477 observations deleted)

{com}. merge m:1 icpsr using "SenateAllLeadersFirst.dta"
{res}
{txt}{col 5}Result{col 33}Number of obs
{col 5}{hline 41}
{col 5}Not matched{col 30}{res}           7,787
{txt}{col 9}from master{col 30}{res}           7,787{txt}  (_merge==1)
{col 9}from using{col 30}{res}               0{txt}  (_merge==2)

{col 5}Matched{col 30}{res}             439{txt}  (_merge==3)
{col 5}{hline 41}

{com}. keep if _merge == 3
{txt}(7,787 observations deleted)

{com}. drop _merge
{txt}
{com}. *Kenneth Wherry was party whip in first Congress, so use his score from his first Congress
. replace firstcongasleader = firstcongasleader + 1 if icpsr == 9998
{txt}(5 real changes made)

{com}. drop if congress >= firstcongasleader
{txt}(254 observations deleted)

{com}. collapse cvp_gls_adjusted, by(icpsr)
{res}{txt}
{com}. rename cvp_gls_adjusted ideology
{res}{txt}
{com}. save "SenateAllLeadersIdeologies.dta", replace
{txt}{p 0 4 2}
(file {bf}
SenateAllLeadersIdeologies.dta{rm}
not found)
{p_end}
{p 0 4 2}
file {bf}
SenateAllLeadersIdeologies.dta{rm}
saved
{p_end}

{com}. clear
{txt}
{com}. use "SenateAllLeadersCleaned.dta"
{txt}
{com}. merge m:1 icpsr using "SenateAllLeadersIdeologies.dta"
{res}
{txt}{col 5}Result{col 33}Number of obs
{col 5}{hline 41}
{col 5}Not matched{col 30}{res}               0
{txt}{col 5}Matched{col 30}{res}             173{txt}  (_merge==3)
{col 5}{hline 41}

{com}. drop _merge
{txt}
{com}. *no Republican Senate whip in 77th congress, just focus on 78th through 117th
. keep if congress >= 78 & congress <= 117
{txt}(13 observations deleted)

{com}. egen party_cong = group(dem congress)
{txt}
{com}. g leader_cvp = ideology if leader == 1
{txt}(80 missing values generated)

{com}. g otherleader_cvp = ideology if whip == 1
{txt}(80 missing values generated)

{com}. collapse leader_cvp otherleader_cvp dem congress, by(party_cong)
{res}{txt}
{com}. drop party_cong
{txt}
{com}. save "SenateAllLeaderIdeologiesByPartyCongress.dta", replace
{txt}{p 0 4 2}
(file {bf}
SenateAllLeaderIdeologiesByPartyCongress.dta{rm}
not found)
{p_end}
{p 0 4 2}
file {bf}
SenateAllLeaderIdeologiesByPartyCongress.dta{rm}
saved
{p_end}

{com}. clear
{txt}
{com}. use "CleanedRollCallData.dta"
{txt}
{com}. keep if house == 0
{txt}(12,461,813 observations deleted)

{com}. merge m:1 icpsr congress using "SenateAllLeadersCleaned.dta" 
{res}
{txt}{col 5}Result{col 33}Number of obs
{col 5}{hline 41}
{col 5}Not matched{col 30}{res}       2,071,038
{txt}{col 9}from master{col 30}{res}       2,070,947{txt}  (_merge==1)
{col 9}from using{col 30}{res}              91{txt}  (_merge==2)

{col 5}Matched{col 30}{res}          44,598{txt}  (_merge==3)
{col 5}{hline 41}

{com}. keep if _merge == 1
{txt}(44,689 observations deleted)

{com}. drop _merge
{txt}
{com}. drop leader_*
{txt}
{com}. merge m:1 dem congress using "SenateAllLeaderIdeologiesByPartyCongress.dta"
{res}
{txt}{col 5}Result{col 33}Number of obs
{col 5}{hline 41}
{col 5}Not matched{col 30}{res}          32,562
{txt}{col 9}from master{col 30}{res}          32,562{txt}  (_merge==1)
{col 9}from using{col 30}{res}               0{txt}  (_merge==2)

{col 5}Matched{col 30}{res}       2,038,385{txt}  (_merge==3)
{col 5}{hline 41}

{com}. tab congress _merge

           {txt}{c |} Matching result from
           {c |}         merge
  congress {c |} Master on  Matched ( {c |}     Total
{hline 11}{c +}{hline 22}{c +}{hline 10}
        76 {c |}{res}    19,642          0 {txt}{c |}{res}    19,642 
{txt}        77 {c |}{res}    12,920          0 {txt}{c |}{res}    12,920 
{txt}        78 {c |}{res}         0     15,999 {txt}{c |}{res}    15,999 
{txt}        79 {c |}{res}         0     17,902 {txt}{c |}{res}    17,902 
{txt}        80 {c |}{res}         0     19,953 {txt}{c |}{res}    19,953 
{txt}        81 {c |}{res}         0     36,703 {txt}{c |}{res}    36,703 
{txt}        82 {c |}{res}         0     24,273 {txt}{c |}{res}    24,273 
{txt}        83 {c |}{res}         0     21,025 {txt}{c |}{res}    21,025 
{txt}        84 {c |}{res}         0     16,580 {txt}{c |}{res}    16,580 
{txt}        85 {c |}{res}         0     23,640 {txt}{c |}{res}    23,640 
{txt}        86 {c |}{res}         0     34,480 {txt}{c |}{res}    34,480 
{txt}        87 {c |}{res}         0     37,197 {txt}{c |}{res}    37,197 
{txt}        88 {c |}{res}         0     47,095 {txt}{c |}{res}    47,095 
{txt}        89 {c |}{res}         0     40,505 {txt}{c |}{res}    40,505 
{txt}        90 {c |}{res}         0     46,465 {txt}{c |}{res}    46,465 
{txt}        91 {c |}{res}         0     49,689 {txt}{c |}{res}    49,689 
{txt}        92 {c |}{res}         0     67,828 {txt}{c |}{res}    67,828 
{txt}        93 {c |}{res}         0     86,068 {txt}{c |}{res}    86,068 
{txt}        94 {c |}{res}         0     98,806 {txt}{c |}{res}    98,806 
{txt}        95 {c |}{res}         0     93,131 {txt}{c |}{res}    93,131 
{txt}        96 {c |}{res}         0     82,760 {txt}{c |}{res}    82,760 
{txt}        97 {c |}{res}         0     77,551 {txt}{c |}{res}    77,551 
{txt}        98 {c |}{res}         0     52,910 {txt}{c |}{res}    52,910 
{txt}        99 {c |}{res}         0     63,964 {txt}{c |}{res}    63,964 
{txt}       100 {c |}{res}         0     61,784 {txt}{c |}{res}    61,784 
{txt}       101 {c |}{res}         0     49,636 {txt}{c |}{res}    49,636 
{txt}       102 {c |}{res}         0     45,554 {txt}{c |}{res}    45,554 
{txt}       103 {c |}{res}         0     61,931 {txt}{c |}{res}    61,931 
{txt}       104 {c |}{res}         0     77,034 {txt}{c |}{res}    77,034 
{txt}       105 {c |}{res}         0     49,616 {txt}{c |}{res}    49,616 
{txt}       106 {c |}{res}         0     55,102 {txt}{c |}{res}    55,102 
{txt}       107 {c |}{res}         0     45,620 {txt}{c |}{res}    45,620 
{txt}       108 {c |}{res}         0     49,351 {txt}{c |}{res}    49,351 
{txt}       109 {c |}{res}         0     49,129 {txt}{c |}{res}    49,129 
{txt}       110 {c |}{res}         0     51,859 {txt}{c |}{res}    51,859 
{txt}       111 {c |}{res}         0     58,068 {txt}{c |}{res}    58,068 
{txt}       112 {c |}{res}         0     40,404 {txt}{c |}{res}    40,404 
{txt}       113 {c |}{res}         0     51,507 {txt}{c |}{res}    51,507 
{txt}       114 {c |}{res}         0     40,054 {txt}{c |}{res}    40,054 
{txt}       115 {c |}{res}         0     51,027 {txt}{c |}{res}    51,027 
{txt}       116 {c |}{res}         0     62,495 {txt}{c |}{res}    62,495 
{txt}       117 {c |}{res}         0     83,690 {txt}{c |}{res}    83,690 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
     Total {c |}{res}    32,562  2,038,385 {txt}{c |}{res} 2,070,947 
{txt}
{com}. keep if _merge == 3
{txt}(32,562 observations deleted)

{com}. drop _merge
{txt}
{com}. keep congress house rollnumber icpsr dem conservative bill-party_chamber_congress leader_cvp otherleader_cvp
{txt}
{com}. save "CleanedRollCallData_SenateAllLeaders.dta", replace
{txt}{p 0 4 2}
(file {bf}
CleanedRollCallData_SenateAllLeaders.dta{rm}
not found)
{p_end}
{p 0 4 2}
file {bf}
CleanedRollCallData_SenateAllLeaders.dta{rm}
saved
{p_end}

{com}. clear
{txt}
{com}. use "HouseAllLeaders.dta"
{txt}
{com}. reshape long leader whip ml, i(icpsr) j(num)
{res}{txt}(j = 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16)
(variable {bf:ml9} not found)
(variable {bf:ml10} not found)
(variable {bf:leader11} not found)
(variable {bf:ml11} not found)
(variable {bf:leader12} not found)
(variable {bf:ml12} not found)
(variable {bf:leader13} not found)
(variable {bf:ml13} not found)
(variable {bf:leader14} not found)
(variable {bf:ml14} not found)
(variable {bf:leader15} not found)
(variable {bf:ml15} not found)
(variable {bf:leader16} not found)
(variable {bf:ml16} not found)

Data{col 36}Wide{col 43}->{col 48}Long
{hline 77}
Number of observations     {res}          41   {txt}->   {res}656         
{txt}Number of variables        {res}          37   {txt}->   {res}7           
{txt}j variable (16 values)                    ->   {res}num
{txt}xij variables:
           {res}leader1 leader2 ... leader16   {txt}->   {res}leader
                 whip1 whip2 ... whip16   {txt}->   {res}whip
                       ml1 ml2 ... ml16   {txt}->   {res}ml
{txt}{hline 77}

{com}. drop if whip == . & leader == . & ml == .
{txt}(482 observations deleted)

{com}. drop num
{txt}
{com}. preserve
{txt}
{com}. drop leader ml
{txt}
{com}. drop if whip == .
{txt}(81 observations deleted)

{com}. rename whip congress
{res}{txt}
{com}. g whip = 1
{txt}
{com}. save "whip.dta", replace
{txt}{p 0 4 2}
file {bf}
whip.dta{rm}
saved
{p_end}

{com}. restore
{txt}
{com}. preserve
{txt}
{com}. drop whip leader
{txt}
{com}. drop if ml == .
{txt}(131 observations deleted)

{com}. rename ml congress
{res}{txt}
{com}. g ml = 1
{txt}
{com}. save "ml.dta", replace
{txt}{p 0 4 2}
(file {bf}
ml.dta{rm}
not found)
{p_end}
{p 0 4 2}
file {bf}
ml.dta{rm}
saved
{p_end}

{com}. restore
{txt}
{com}. drop whip ml
{txt}
{com}. drop if leader == .
{txt}(89 observations deleted)

{com}. rename leader congress
{res}{txt}
{com}. g leader = 1
{txt}
{com}. append using "whip.dta"
{txt}
{com}. append using "ml.dta" 
{txt}
{com}. sort icpsr congress
{txt}
{com}. replace leader = 0 if leader == .
{txt}(136 real changes made)

{com}. g otherleader = whip == 1 | ml == 1
{txt}
{com}. drop whip ml
{txt}
{com}. save "HouseAllLeadersCleaned.dta", replace
{txt}{p 0 4 2}
(file {bf}
HouseAllLeadersCleaned.dta{rm}
not found)
{p_end}
{p 0 4 2}
file {bf}
HouseAllLeadersCleaned.dta{rm}
saved
{p_end}

{com}. egen firstcongasleader = min(congress), by(icpsr)
{txt}
{com}. keep icpsr name firstcong
{txt}
{com}. sort icpsr
{txt}
{com}. drop if icpsr == icpsr[_n-1]
{txt}(180 observations deleted)

{com}. save "HouseAllLeadersFirst.dta", replace
{txt}{p 0 4 2}
(file {bf}
HouseAllLeadersFirst.dta{rm}
not found)
{p_end}
{p 0 4 2}
file {bf}
HouseAllLeadersFirst.dta{rm}
saved
{p_end}

{com}. clear
{txt}
{com}. use "CVP_1_117.dta"
{txt}
{com}. rename name name2
{res}{txt}
{com}. keep chamber congress icpsr party cvp_gls_adjusted name2
{txt}
{com}. keep if chamber == "House"
{txt}(9,703 observations deleted)

{com}. keep if party == 100 | party == 200
{txt}(5,610 observations deleted)

{com}. merge m:1 icpsr using "HouseAllLeadersFirst.dta"
{res}
{txt}{col 5}Result{col 33}Number of obs
{col 5}{hline 41}
{col 5}Not matched{col 30}{res}          33,702
{txt}{col 9}from master{col 30}{res}          33,702{txt}  (_merge==1)
{col 9}from using{col 30}{res}               0{txt}  (_merge==2)

{col 5}Matched{col 30}{res}             489{txt}  (_merge==3)
{col 5}{hline 41}

{com}. keep if _merge == 3
{txt}(33,702 observations deleted)

{com}. drop _merge
{txt}
{com}. drop if congress >= firstcongasleader
{txt}(232 observations deleted)

{com}. collapse cvp_gls_adjusted, by(icpsr)
{res}{txt}
{com}. rename cvp_gls_adjusted ideology
{res}{txt}
{com}. save "HouseAllLeadersIdeologies.dta", replace
{txt}{p 0 4 2}
(file {bf}
HouseAllLeadersIdeologies.dta{rm}
not found)
{p_end}
{p 0 4 2}
file {bf}
HouseAllLeadersIdeologies.dta{rm}
saved
{p_end}

{com}. clear
{txt}
{com}. use "HouseAllLeadersCleaned.dta"
{txt}
{com}. merge m:1 icpsr using "HouseAllLeadersIdeologies.dta"
{res}
{txt}{col 5}Result{col 33}Number of obs
{col 5}{hline 41}
{col 5}Not matched{col 30}{res}               0
{txt}{col 5}Matched{col 30}{res}             221{txt}  (_merge==3)
{col 5}{hline 41}

{com}. drop _merge
{txt}
{com}. keep if congress >= 77 & congress <= 117
{txt}(17 observations deleted)

{com}. egen party_cong = group(dem congress)
{txt}
{com}. g leader_cvp = ideology if leader == 1
{txt}(122 missing values generated)

{com}. g otherleader_cvp = ideology if otherleader == 1
{txt}(82 missing values generated)

{com}. collapse leader_cvp otherleader_cvp dem congress, by(party_cong)
{res}{txt}
{com}. drop party_cong
{txt}
{com}. save "HouseAllLeaderIdeologiesByPartyCongress.dta", replace
{txt}{p 0 4 2}
(file {bf}
HouseAllLeaderIdeologiesByPartyCongress.dta{rm}
not found)
{p_end}
{p 0 4 2}
file {bf}
HouseAllLeaderIdeologiesByPartyCongress.dta{rm}
saved
{p_end}

{com}. clear
{txt}
{com}. use "CleanedRollCallData.dta"
{txt}
{com}. keep if house == 1
{txt}(2,115,545 observations deleted)

{com}. merge m:1 icpsr congress using "HouseAllLeadersCleaned.dta" 
{res}
{txt}{col 5}Result{col 33}Number of obs
{col 5}{hline 41}
{col 5}Not matched{col 30}{res}      12,375,132
{txt}{col 9}from master{col 30}{res}      12,375,035{txt}  (_merge==1)
{col 9}from using{col 30}{res}              97{txt}  (_merge==2)

{col 5}Matched{col 30}{res}          86,778{txt}  (_merge==3)
{col 5}{hline 41}

{com}. keep if _merge == 1
{txt}(86,875 observations deleted)

{com}. drop _merge
{txt}
{com}. drop leader_*
{txt}
{com}. merge m:1 dem congress using "HouseAllLeaderIdeologiesByPartyCongress.dta"
{res}
{txt}{col 5}Result{col 33}Number of obs
{col 5}{hline 41}
{col 5}Not matched{col 30}{res}          79,837
{txt}{col 9}from master{col 30}{res}          79,837{txt}  (_merge==1)
{col 9}from using{col 30}{res}               0{txt}  (_merge==2)

{col 5}Matched{col 30}{res}      12,295,198{txt}  (_merge==3)
{col 5}{hline 41}

{com}. tab congress _merge

           {txt}{c |} Matching result from
           {c |}         merge
  congress {c |} Master on  Matched ( {c |}     Total
{hline 11}{c +}{hline 22}{c +}{hline 10}
        76 {c |}{res}    79,837          0 {txt}{c |}{res}    79,837 
{txt}        77 {c |}{res}         0     45,537 {txt}{c |}{res}    45,537 
{txt}        78 {c |}{res}         0     49,973 {txt}{c |}{res}    49,973 
{txt}        79 {c |}{res}         0     75,725 {txt}{c |}{res}    75,725 
{txt}        80 {c |}{res}         0     58,799 {txt}{c |}{res}    58,799 
{txt}        81 {c |}{res}         0     95,566 {txt}{c |}{res}    95,566 
{txt}        82 {c |}{res}         0     62,384 {txt}{c |}{res}    62,384 
{txt}        83 {c |}{res}         0     50,533 {txt}{c |}{res}    50,533 
{txt}        84 {c |}{res}         0     55,094 {txt}{c |}{res}    55,094 
{txt}        85 {c |}{res}         0     73,095 {txt}{c |}{res}    73,095 
{txt}        86 {c |}{res}         0     69,363 {txt}{c |}{res}    69,363 
{txt}        87 {c |}{res}         0     84,862 {txt}{c |}{res}    84,862 
{txt}        88 {c |}{res}         0     84,839 {txt}{c |}{res}    84,839 
{txt}        89 {c |}{res}         0    130,351 {txt}{c |}{res}   130,351 
{txt}        90 {c |}{res}         0    162,655 {txt}{c |}{res}   162,655 
{txt}        91 {c |}{res}         0    147,996 {txt}{c |}{res}   147,996 
{txt}        92 {c |}{res}         0    223,578 {txt}{c |}{res}   223,578 
{txt}        93 {c |}{res}         0    396,548 {txt}{c |}{res}   396,548 
{txt}        94 {c |}{res}         0    468,063 {txt}{c |}{res}   468,063 
{txt}        95 {c |}{res}         0    569,132 {txt}{c |}{res}   569,132 
{txt}        96 {c |}{res}         0    472,537 {txt}{c |}{res}   472,537 
{txt}        97 {c |}{res}         0    299,842 {txt}{c |}{res}   299,842 
{txt}        98 {c |}{res}         0    338,546 {txt}{c |}{res}   338,546 
{txt}        99 {c |}{res}         0    337,716 {txt}{c |}{res}   337,716 
{txt}       100 {c |}{res}         0    339,767 {txt}{c |}{res}   339,767 
{txt}       101 {c |}{res}         0    333,041 {txt}{c |}{res}   333,041 
{txt}       102 {c |}{res}         0    339,837 {txt}{c |}{res}   339,837 
{txt}       103 {c |}{res}         0    426,885 {txt}{c |}{res}   426,885 
{txt}       104 {c |}{res}         0    515,607 {txt}{c |}{res}   515,607 
{txt}       105 {c |}{res}         0    442,170 {txt}{c |}{res}   442,170 
{txt}       106 {c |}{res}         0    438,437 {txt}{c |}{res}   438,437 
{txt}       107 {c |}{res}         0    332,299 {txt}{c |}{res}   332,299 
{txt}       108 {c |}{res}         0    401,193 {txt}{c |}{res}   401,193 
{txt}       109 {c |}{res}         0    427,380 {txt}{c |}{res}   427,380 
{txt}       110 {c |}{res}         0    635,819 {txt}{c |}{res}   635,819 
{txt}       111 {c |}{res}         0    498,949 {txt}{c |}{res}   498,949 
{txt}       112 {c |}{res}         0    629,547 {txt}{c |}{res}   629,547 
{txt}       113 {c |}{res}         0    455,008 {txt}{c |}{res}   455,008 
{txt}       114 {c |}{res}         0    505,501 {txt}{c |}{res}   505,501 
{txt}       115 {c |}{res}         0    451,245 {txt}{c |}{res}   451,245 
{txt}       116 {c |}{res}         0    370,454 {txt}{c |}{res}   370,454 
{txt}       117 {c |}{res}         0    399,325 {txt}{c |}{res}   399,325 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
     Total {c |}{res}    79,837 12,295,198 {txt}{c |}{res}12,375,035 
{txt}
{com}. keep if _merge == 3
{txt}(79,837 observations deleted)

{com}. drop _merge
{txt}
{com}. keep congress house rollnumber icpsr dem conservative bill-party_chamber_congress leader_cvp otherleader_cvp
{txt}
{com}. append using "CleanedRollCallData_SenateAllLeaders.dta"
{txt}
{com}. keep if congress >= 78 & congress <= 116
{txt}(528,552 observations deleted)

{com}. areg conservative leader_cvp, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}    .03924
{txt}Iteration 2:  Maximum absolute difference ={res}    .03242
{txt}Iteration 3:  Maximum absolute difference ={res}    .01604
{txt}Iteration 4:  Maximum absolute difference ={res}   .008142
{txt}Iteration 5:  Maximum absolute difference ={res}   .002698
{txt}Iteration 6:  Maximum absolute difference ={res}  .0008995
{txt}Iteration 7:  Maximum absolute difference ={res}  .0005247
{txt}Iteration 8:  Maximum absolute difference ={res}  .0004608
{txt}Iteration 9:  Maximum absolute difference ={res}  .0001578
{txt}Iteration 10: Maximum absolute difference ={res}  .0001452
{txt}Iteration 11: Maximum absolute difference ={res} .00008428
{txt}Iteration 12: Maximum absolute difference ={res} 8.607e-06
{txt}Iteration 13: Maximum absolute difference ={res} 4.358e-06
{txt}Iteration 14: Maximum absolute difference ={res} 5.082e-06
{txt}Iteration 15: Maximum absolute difference ={res} 3.067e-06
{txt}Iteration 16: Maximum absolute difference ={res} 7.575e-07
{txt}Iteration 17: Maximum absolute difference ={res} 1.883e-07
{txt}Iteration 18: Maximum absolute difference ={res} 4.918e-08
{txt}Iteration 19: Maximum absolute difference ={res} 3.123e-09

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}     .0494
{txt}Iteration 2:  Maximum absolute difference ={res}    .02038
{txt}Iteration 3:  Maximum absolute difference ={res}    .01628
{txt}Iteration 4:  Maximum absolute difference ={res}   .007818
{txt}Iteration 5:  Maximum absolute difference ={res}   .005851
{txt}Iteration 6:  Maximum absolute difference ={res}   .005826
{txt}Iteration 7:  Maximum absolute difference ={res}    .00203
{txt}Iteration 8:  Maximum absolute difference ={res}  .0006347
{txt}Iteration 9:  Maximum absolute difference ={res}  .0001451
{txt}Iteration 10: Maximum absolute difference ={res}  .0001341
{txt}Iteration 11: Maximum absolute difference ={res}  .0001044
{txt}Iteration 12: Maximum absolute difference ={res} .00001895
{txt}Iteration 13: Maximum absolute difference ={res} .00001868
{txt}Iteration 14: Maximum absolute difference ={res} 5.999e-06
{txt}Iteration 15: Maximum absolute difference ={res} 1.772e-06
{txt}Iteration 16: Maximum absolute difference ={res} 4.541e-07
{txt}Iteration 17: Maximum absolute difference ={res} 2.127e-07
{txt}Iteration 18: Maximum absolute difference ={res} 2.594e-08
{txt}Iteration 19: Maximum absolute difference ={res} 2.896e-09

{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 13:Number of obs}{col 66} = {res}{ralign 10:13,805,031}
{txt}{col 53}{lalign 13:Cluster comb.}{col 66} = {res}{ralign 10:3}
{txt}{col 1}Clusters per comb.:{col 53}{lalign 13:F({res:1}, {res:155})}{col 66} = {res}{ralign 10:26.77}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 6:156}{txt}{col 53}{lalign 13:Prob > F}{col 66} = {res}{ralign 10:0.0000}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 6:8,306}{txt}{col 53}{lalign 13:R-squared}{col 66} = {res}{ralign 10:0.5532}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 6:20,870}{txt}{col 53}{lalign 13:Adj R-squared}{col 66} = {res}{ralign 10:0.5514}
{txt}{col 53}{lalign 13:Root MSE}{col 66} = {res}{ralign 10:0.3333}

{txt}{ralign 78:(Std. err. adjusted for multiway clustering)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}conservative{col 14}{c |} Coefficient{col 26}  std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}leader_cvp {c |}{col 14}{res}{space 2} .3671982{col 26}{space 2} .0709736{col 37}{space 1}    5.17{col 46}{space 3}0.000{col 54}{space 4} .2269979{col 67}{space 3} .5073984
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}   .37845{col 26}{space 2} .0142373{col 37}{space 1}   26.58{col 46}{space 3}0.000{col 54}{space 4} .3503257{col 67}{space 3} .4065742
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "OtherLeaders.txt", replace 2aster dec(3) sortvar(leader_cvp otherleader_cvp)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "OtherLeaders.txt""':seeout}

{com}. areg conservative otherleader_cvp, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}    .03924
{txt}Iteration 2:  Maximum absolute difference ={res}    .03242
{txt}Iteration 3:  Maximum absolute difference ={res}    .01604
{txt}Iteration 4:  Maximum absolute difference ={res}   .008142
{txt}Iteration 5:  Maximum absolute difference ={res}   .002698
{txt}Iteration 6:  Maximum absolute difference ={res}  .0008995
{txt}Iteration 7:  Maximum absolute difference ={res}  .0005247
{txt}Iteration 8:  Maximum absolute difference ={res}  .0004608
{txt}Iteration 9:  Maximum absolute difference ={res}  .0001578
{txt}Iteration 10: Maximum absolute difference ={res}  .0001452
{txt}Iteration 11: Maximum absolute difference ={res} .00008428
{txt}Iteration 12: Maximum absolute difference ={res} 8.607e-06
{txt}Iteration 13: Maximum absolute difference ={res} 4.358e-06
{txt}Iteration 14: Maximum absolute difference ={res} 5.082e-06
{txt}Iteration 15: Maximum absolute difference ={res} 3.067e-06
{txt}Iteration 16: Maximum absolute difference ={res} 7.575e-07
{txt}Iteration 17: Maximum absolute difference ={res} 1.883e-07
{txt}Iteration 18: Maximum absolute difference ={res} 4.918e-08
{txt}Iteration 19: Maximum absolute difference ={res} 3.123e-09

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}    .05824
{txt}Iteration 2:  Maximum absolute difference ={res}    .02916
{txt}Iteration 3:  Maximum absolute difference ={res}    .01806
{txt}Iteration 4:  Maximum absolute difference ={res}   .008841
{txt}Iteration 5:  Maximum absolute difference ={res}   .008935
{txt}Iteration 6:  Maximum absolute difference ={res}   .007235
{txt}Iteration 7:  Maximum absolute difference ={res}   .002187
{txt}Iteration 8:  Maximum absolute difference ={res}   .001161
{txt}Iteration 9:  Maximum absolute difference ={res}  .0003874
{txt}Iteration 10: Maximum absolute difference ={res}  .0002199
{txt}Iteration 11: Maximum absolute difference ={res} .00005095
{txt}Iteration 12: Maximum absolute difference ={res}  .0000846
{txt}Iteration 13: Maximum absolute difference ={res} .00003357
{txt}Iteration 14: Maximum absolute difference ={res} 4.852e-06
{txt}Iteration 15: Maximum absolute difference ={res} 1.113e-06
{txt}Iteration 16: Maximum absolute difference ={res} 1.635e-07
{txt}Iteration 17: Maximum absolute difference ={res} 9.183e-08
{txt}Iteration 18: Maximum absolute difference ={res} 6.065e-09

{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 13:Number of obs}{col 66} = {res}{ralign 10:13,805,031}
{txt}{col 53}{lalign 13:Cluster comb.}{col 66} = {res}{ralign 10:3}
{txt}{col 1}Clusters per comb.:{col 53}{lalign 13:F({res:1}, {res:155})}{col 66} = {res}{ralign 10:2.05}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 6:156}{txt}{col 53}{lalign 13:Prob > F}{col 66} = {res}{ralign 10:0.1545}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 6:8,306}{txt}{col 53}{lalign 13:R-squared}{col 66} = {res}{ralign 10:0.5529}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 6:20,870}{txt}{col 53}{lalign 13:Adj R-squared}{col 66} = {res}{ralign 10:0.5511}
{txt}{col 53}{lalign 13:Root MSE}{col 66} = {res}{ralign 10:0.3334}

{txt}{ralign 81:(Std. err. adjusted for multiway clustering)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}   conservative{col 17}{c |} Coefficient{col 29}  std. err.{col 41}      t{col 49}   P>|t|{col 57}     [95% con{col 70}f. interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
otherleader_cvp {c |}{col 17}{res}{space 2}-.1341058{col 29}{space 2} .0937242{col 40}{space 1}   -1.43{col 49}{space 3}0.154{col 57}{space 4}-.3192473{col 70}{space 3} .0510358
{txt}{space 10}_cons {c |}{col 17}{res}{space 2}  .479328{col 29}{space 2}  .020243{col 40}{space 1}   23.68{col 49}{space 3}0.000{col 57}{space 4} .4393403{col 70}{space 3} .5193157
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "OtherLeaders.txt", append 2aster dec(3) sortvar(leader_cvp otherleader_cvp)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "OtherLeaders.txt""':seeout}

{com}. areg conservative leader_cvp otherleader_cvp, a(member_party_chamber bill) vce(cluster member_party_chamber party_chamber_congress)
{res}
{txt}Halperin APM for regression coefficients:

{txt}Dependent variable:
{txt}Iteration 1:  Maximum absolute difference ={res}    .03924
{txt}Iteration 2:  Maximum absolute difference ={res}    .03242
{txt}Iteration 3:  Maximum absolute difference ={res}    .01604
{txt}Iteration 4:  Maximum absolute difference ={res}   .008142
{txt}Iteration 5:  Maximum absolute difference ={res}   .002698
{txt}Iteration 6:  Maximum absolute difference ={res}  .0008995
{txt}Iteration 7:  Maximum absolute difference ={res}  .0005247
{txt}Iteration 8:  Maximum absolute difference ={res}  .0004608
{txt}Iteration 9:  Maximum absolute difference ={res}  .0001578
{txt}Iteration 10: Maximum absolute difference ={res}  .0001452
{txt}Iteration 11: Maximum absolute difference ={res} .00008428
{txt}Iteration 12: Maximum absolute difference ={res} 8.607e-06
{txt}Iteration 13: Maximum absolute difference ={res} 4.358e-06
{txt}Iteration 14: Maximum absolute difference ={res} 5.082e-06
{txt}Iteration 15: Maximum absolute difference ={res} 3.067e-06
{txt}Iteration 16: Maximum absolute difference ={res} 7.575e-07
{txt}Iteration 17: Maximum absolute difference ={res} 1.883e-07
{txt}Iteration 18: Maximum absolute difference ={res} 4.918e-08
{txt}Iteration 19: Maximum absolute difference ={res} 3.123e-09

{txt}Independent variables:
{txt}Iteration 1:  Maximum absolute difference ={res}    .05824
{txt}Iteration 2:  Maximum absolute difference ={res}    .02916
{txt}Iteration 3:  Maximum absolute difference ={res}    .01806
{txt}Iteration 4:  Maximum absolute difference ={res}   .008841
{txt}Iteration 5:  Maximum absolute difference ={res}   .008935
{txt}Iteration 6:  Maximum absolute difference ={res}   .007235
{txt}Iteration 7:  Maximum absolute difference ={res}   .002187
{txt}Iteration 8:  Maximum absolute difference ={res}   .001161
{txt}Iteration 9:  Maximum absolute difference ={res}  .0003874
{txt}Iteration 10: Maximum absolute difference ={res}  .0002199
{txt}Iteration 11: Maximum absolute difference ={res}  .0001044
{txt}Iteration 12: Maximum absolute difference ={res}  .0000846
{txt}Iteration 13: Maximum absolute difference ={res} .00003357
{txt}Iteration 14: Maximum absolute difference ={res} 5.999e-06
{txt}Iteration 15: Maximum absolute difference ={res} 1.772e-06
{txt}Iteration 16: Maximum absolute difference ={res} 4.541e-07
{txt}Iteration 17: Maximum absolute difference ={res} 2.127e-07
{txt}Iteration 18: Maximum absolute difference ={res} 2.594e-08
{txt}Iteration 19: Maximum absolute difference ={res} 2.896e-09

{txt}{col 1}Linear regression, absorbing indicators{col 53}{lalign 13:Number of obs}{col 66} = {res}{ralign 10:13,805,031}
{txt}{col 53}{lalign 13:Cluster comb.}{col 66} = {res}{ralign 10:3}
{txt}{col 1}Clusters per comb.:{col 53}{lalign 13:F({res:2}, {res:155})}{col 66} = {res}{ralign 10:17.39}
{txt}{col 1}{lalign 5:  min}{col 6} = {res}{ralign 6:156}{txt}{col 53}{lalign 13:Prob > F}{col 66} = {res}{ralign 10:0.0000}
{txt}{col 1}{lalign 5:  avg}{col 6} = {res}{ralign 6:8,306}{txt}{col 53}{lalign 13:R-squared}{col 66} = {res}{ralign 10:0.5532}
{txt}{col 1}{lalign 5:  max}{col 6} = {res}{ralign 6:20,870}{txt}{col 53}{lalign 13:Adj R-squared}{col 66} = {res}{ralign 10:0.5514}
{txt}{col 53}{lalign 13:Root MSE}{col 66} = {res}{ralign 10:0.3333}

{txt}{ralign 81:(Std. err. adjusted for multiway clustering)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}   conservative{col 17}{c |} Coefficient{col 29}  std. err.{col 41}      t{col 49}   P>|t|{col 57}     [95% con{col 70}f. interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}leader_cvp {c |}{col 17}{res}{space 2} .3504534{col 29}{space 2} .0596568{col 40}{space 1}    5.87{col 49}{space 3}0.000{col 57}{space 4} .2326081{col 70}{space 3} .4682987
{txt}otherleader_cvp {c |}{col 17}{res}{space 2}-.0557616{col 29}{space 2} .0896391{col 40}{space 1}   -0.62{col 49}{space 3}0.535{col 57}{space 4}-.2328335{col 70}{space 3} .1213102
{txt}{space 10}_cons {c |}{col 17}{res}{space 2}  .393629{col 29}{space 2} .0207552{col 40}{space 1}   18.97{col 49}{space 3}0.000{col 57}{space 4} .3526294{col 70}{space 3} .4346286
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 4 2}Cluster combinations formed by {bf:member_party_chamber} and {bf:party_chamber_congress}.{p_end}

{com}. outreg2 using "OtherLeaders.txt", append 2aster dec(3) sortvar(leader_cvp otherleader_cvp)
{browse `"C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data"' :dir} : {txt}{stata `"seeout using "OtherLeaders.txt""':seeout}

{com}. 
. 
. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\agfowler\Dropbox\Party Leaders\Fowler Leaders Replication Data\partyleaderslog.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res}12 Nov 2025, 22:05:05
{txt}{.-}
{smcl}
{txt}{sf}{ul off}